In our latest 10 Minutes With, we’re spotlighting Albana Adili — the warm, detail‑driven force who keeps RedCloud running smoothly behind the scenes. Albana supports several core operational functions, from onboarding and HR coordination to light IT support and day‑to‑day office management. In just two months, she’s already become a trusted partner to consultants across the country and globe, bringing curiosity, care, and a genuine love of people to every interaction. Outside of work, she’s all about good stories, good food, and good company — whether she’s exploring Washington trails, discovering new shows with her fiancé, or tracking down the perfect cider. Learn more about Albana in her own words below. Describe your role and what you do in a nutshell In my role, I support several key operational areas that keep our people and our office running smoothly. A large part of my work centers on HR coordination, especially onboarding. I help new team members get settled, ensure their information is accurately captured in our systems, and maintain the various platforms we use for employee management. I also support light IT needs, making sure consultants have the equipment and access they need to hit the ground running. On top of that, I manage day‑to‑day office operations - everything from ordering everyone’s favorite snacks to troubleshooting the little issues that pop up in a busy workspace. What do you enjoy most or find especially interesting about your current role? Working with our consultants has been the most fascinating part of my role so far. In my initial time at RedCloud, I’ve already met consultants from all over the country, each with their own unique background, expertise, and career journey. Some are early in their careers; others are seasoned professionals, but they all bring something distinct to the table. Getting to know them and learning about their work style has been incredibly interesting! Share your go‑to methods for professional development or personal growth For professional development, I’m a big believer in using the resources you have access to. If you can, take advantage of LinkedIn Learning ; it’s full of courses that can help you build both technical and soft skills. The platform itself is a great place to connect with people, follow thought leaders, and absorb useful insights. I also think continuing education at local colleges or universities can be incredibly valuable. Earning certifications in this way can really set you up for success. For personal growth, I rely heavily on the people in my life. Staying close to friends and family, asking for advice, and surrounding yourself with genuine, grounded people can teach you so much. I also think self‑reflection is essential - taking time to think about where you’ve been, who you are now, and who you want to become. For me, that often happens when I’m alone with my thoughts on a hike or a long walk. Washington makes that easy, with so many beautiful places to wander. How would you describe RedCloud’s company culture? RedCloud strikes a great balance between working hard and genuinely enjoying the people around you. Everyone is busy and focused on delivering great work, but there’s also a real sense of camaraderie. When we do get a moment to connect, people here are kind, curious, and truly interested in how you’re doing. What’s a piece of obsolete technology you still have a soft spot for? I love rotary phones! One day, I’d love to have a fully functioning, beautifully ornate rotary phone in my home, ideally sitting next to a cozy armchair. I can picture myself spending an entire afternoon calling my mom just to chat about nothing! What’s one thing people don’t know about you that they’d be surprised to discover? I think people would be surprised to learn that the 1970s are my favorite era for music. I'm completely obsessed with Fleetwood Mac - their sound, their style, their whole vibe. They're timeless, and they somehow captured the sound of love and life perfectly, forever. What are you passionate about or enjoy outside of work? Outside of work, I love discovering new TV shows and movies with my fiancé; it’s one of our favorite ways to unwind together. We’re also trying to read more and are always on the lookout for new books to dive into.  I also love spending time with friends and family. We love exploring new breweries (I’m a big cider fan) and trying out new restaurants. Good food, good drinks, and good company make for the best weekends!

In this 10 Minutes With, Nick Root shares how he blends people-focused recruiting with a passion for process optimization. As a Technical Recruiter at RedCloud, he supports consultant placements while exploring tools such as Salesforce and Bullhorn to enhance the team's experience. Nick is most proud of the lasting relationships he’s built throughout his career, and outside of work, he finds joy in vintage wristwatches and overlanding adventures with his wife in the Pacific Northwest. Describe your role and what you do in a nutshell.   I am a Technical Recruiter on RedCloud’s recruiting team. I focus on full-stack recruiting for consultants across our offerings and locations alongside our four other full-stack recruiters. We also work with existing consultants on new project placements and with account managers during proposals and other sales activities.   What do you aim to accomplish professionally this year?   I aim to expand my skill set in operational and process technology, including the optimization of Salesforce, Bullhorn, and other internal tools. I have always been passionate about where people meet processes, and learning more about the tech behind it has been a pleasure this year. I know there are many areas where I can learn, and I aim to continue exploring how our different systems can integrate to enhance both our candidate and employee experiences. In the meantime, it allows me to meet more of our corporate team and consultants and build relationships outside my normal day-to-day.   What are you most proud of in your career so far?   The relationships I’ve built and maintained. The personal and social aspects of recruiting have always drawn me in, and I am motivated by the wonderful people I've met and continue to work with throughout my career. Both those that I have had the pleasure of finding new opportunities for and contacts that I keep up with outside of our active opportunities mean a lot to me, and I feel fortunate to have been able to meet so many talented professionals across different backgrounds, markets, experience levels, and industries.   Tell us about something interesting you've learned recently.   How powerful custom Salesforce formulas can be for my reporting and metrics. With opportunities moving quickly through the system, being able to customize how we calculate overall metrics has been a valuable and interesting skill I've been learning with guidance from our practice leaders. Oh, and orcas can come together for "superpod" family reunions - happening now in Washington!   If you could suggest a book for the entire team to read, what would it be and why?   "Teammate" by David Ross. Growing up a baseball and Cubs fan, this was a must-read for me when the former player published this book. It is a great insight into the behind-the-scenes of the industry, but more importantly, a reflection on what it's like to experience wins and losses as a team, and how the biggest impacts on your teammates often come from the smallest actions.   What's a piece of obsolete technology you still have a soft spot for?   I don't think analog watches are necessarily obsolete, but I've recently found myself diving into the analog (and vintage) wristwatch hobby, and I derive joy from the mechanical movements that keep time and function without electricity. Something about wearing a tiny machine on your wrist is very cool to me.   What's one thing people don't know about you that they would be surprised to discover?   I played the drums in a garage jam band in high school. Everyone knows that I have no musical talent whatsoever, so how I managed to convince actually talented guitar players to play over my random beats is still surprising to me.   What are you passionate about or enjoy outside of work?   My wife and I are indeed a stereotypical PNW couple who love the outdoors. Camping, hiking, and day trips throughout the state have been frequent for us, but we have found our niche in overlanding. We purchased a roof-top tent for my truck and have had a blast exploring the national forest roads and doing "dispersed" camping.

What unfolded inside this innovation division wasn’t just a sprint to fill roles—it was the creation of a talent engine built to scale with the organization’s ambition. As the team grew, so did its operating discipline, leadership cohesion, and long‑term capability. This case study explores how rapid onboarding, embedded guidance, and intentional governance came together to transform a brand‑new function into a mature, strategically aligned engine for innovation. CHALLENGE A newly formed innovation division within a global enterprise faced an urgent mandate: scale rapidly while maintaining strategic alignment, compliance, and operational rigor. With 50 critical roles to fill in just weeks, traditional staffing models were too slow and too fragmented to meet the moment. Co‑employment regulations, evolving job scopes, and inconsistent processes added complexity, making it difficult to onboard talent effectively or ensure alignment with enterprise goals. The client needed more than rapid hiring—they needed a governed, future‑ready talent engine capable of supporting long‑term organizational maturity. SOLUTION We delivered a full‑spectrum people strategy that paired high‑velocity onboarding with strategic enablement. In phase one, we launched an accelerated onboarding motion—placing an average of one contractor per day over 60 days—while screening for mission fit, values alignment, and delivery readiness. In parallel, we embedded leadership to provide continuous assessment, coaching, and real‑time course correction as roles and scopes evolved. To build long‑term leverage, we established a talent incubation model that cultivated individuals for future needs, not just immediate gaps, supported by planned rotations and succession pathways. We strengthened cross‑functional cohesion through structured upskilling workshops and situational‑awareness forums. Governance guardrails mitigated co‑employment risk and introduced repeatable processes for onboarding, performance reviews, and renewals. Throughout the engagement, we balanced tactical execution with strategic enablement—delivering day‑to‑day outcomes while documenting operating mechanisms, decision rights, and metrics to support sustainable scale. Objectives: Stand up an accelerated onboarding motion to fill 50 roles at speed Screen talent for mission fit, values alignment, and delivery readiness Embed leadership to provide continuous assessment and coaching Establish a talent incubation model for future organizational needs Introduce structured upskilling and situational‑awareness forums Implement governance guardrails to reduce co‑employment and compliance risk Document operating mechanisms, decision rights, and metrics to support scale RESULTS Within 45 days, all 50 roles were filled, and the program transitioned from high‑velocity onboarding to disciplined alignment. Embedded leadership increased credibility with executives by demonstrating control, transparency, and measurable outcomes. Governance practices reduced compliance risk and introduced rigor without slowing delivery. The talent incubation model converted contractors into essential contributors, lowering churn and preserving institutional knowledge. Operational continuity drove cost savings through reduced ramp time and fewer re‑placements, while standardized processes improved predictability across workstreams. As the innovation office matured, its influence expanded beyond the initial scope: shared operating mechanisms were adopted across teams, upskilling became routine, and leadership gained real‑time visibility into talent health and delivery. The result was a scalable, governed talent engine that powered innovation today and established the foundation for enterprise growth tomorrow. Discover how Delivery Excellence equips teams with the operating mechanisms, leadership alignment, and execution discipline needed to scale.

We’re excited to share an important milestone in RedCloud Consulting’s continued global growth: the opening of our first European office, based in the United Kingdom (UK). Our work across Europe continues to accelerate as organizations invest heavily in modern digital infrastructure. We’re seeing especially strong demand for expertise in the physical security of data centers, where protecting critical assets is essential to operating responsibly in a data‑ and AI‑driven world. Our teams are deeply engaged in helping clients secure their most important systems while scaling for the future. Our presence in the UK will serve as a strategic hub for our broader European operations, enabling closer collaboration with clients and partners and supporting the continued growth of our consultant community across the region. This evolution reflects the rapid expansion of our European team, whose pioneering work and growing project portfolio have laid a strong foundation for what comes next. “The opportunity across Europe is significant, and we’re only at the beginning,” said Andreas Tabor, RedCloud’s EU Lead. “Our early client partnerships and project success have confirmed both the need for our expertise and the impact we can deliver. Establishing a UK hub allows us to scale faster, deepen relationships, and build on the great work already underway across the region.” As RedCloud continues to expand globally, our focus remains constant: delivering trusted expertise grounded in integrity and transparency, practical solutions, and meaningful impact for clients operating at scale—now with an even stronger presence across Europe. To learn more about RedCloud’s services across the region or to inquire about career opportunities with our growing UK‑based team, please contact us directly.

As 2025 comes to a close, one theme rings true across RedCloud Consulting: this was a breakthrough year for our team, our capabilities, and therefore our clients! From client-facing successes to company-wide achievements, our teams of consultants elevated what’s possible and set the stage for an even stronger 2026. Here’s a quick look at the moments that defined our year. Client Highlights & New Consultant Opportunities RedCloud Goes Global With projects now spanning North America, Europe, Asia, and the Middle East, 2025 marked the year RedCloud became a truly global consultancy. Our ability to deliver consistent, high-impact solutions anywhere in the world reinforces our strength as a trusted partner to organizations of all sizes. Data & AI: Turning Potential Into Performance Our Data & AI practice surged forward in 2025. We partnered with our clients to modernize data estates, build intelligent, secure AI solutions, and help them adopt generative AI responsibly. The result? Our clients have new systems that work smarter, decisions that move faster, and meaningful business impact across industries. We’ll continue to lean into this practice in 2026 as more and more companies seek responsible and practical ways to weave AI into their businesses and products. Physical Security One of RedCloud’s fastest-growing areas of service this year was the design, delivery, and support of physical security systems. This includes cameras, gates, access control, perimeter intrusion detection systems, and the supporting networks for global enterprise companies. With growing infrastructure complexity and importance, security has become even more important, and RedCloud is doing its part. Change Management: Energizing Transformations Transformation never slows—and neither did we. RedCloud’s Business Transformation team guided clients through major organizational shifts, new technologies, and evolving business strategies. With a focus on adoption, readiness, and human-centered experiences, our consultants equipped leaders and employees to navigate change with clarity and confidence. Privacy & Security: Reinforcing Trust in a Digital Era With data risk at an all-time high, our Privacy & Security practices delivered essential stability. RedCloud helped clients strengthen compliance, implement scalable security controls, and build programs rooted in trust. Whether advising on regulatory requirements or enhancing enterprise risk posture, we kept organizations protected in a constantly shifting landscape. A More Diverse Client Base — and More Opportunity Than Ever One of the year’s standout achievements was the widening of our client portfolio. In 2025, RedCloud expanded its reach across healthcare, retail, education, professional services, public sector, and beyond. This diversification not only fueled growth—it unlocked new pathways for our consultants to develop expertise, explore new sectors, and lead meaningful work aligned with their interests. Beyond Client Work: Milestones That Shaped Our Year Some of 2025’s biggest moments happened inside RedCloud itself. Recognizing Future Leaders — Our Annual Scholarship Winner This year, we proudly awarded the 8th annual RedCloud Scholarship in 2025 to Lucy Naiman, a standout student dedicated to leadership and community impact. (Full story: Celebrating the 2025 RedCloud Scholarship Recipient – Lucy Naiman ) Best Place to Work One of our proudest accomplishments: RedCloud was named a Best Place to Work in Consulting and a Remote and Hybrid workplace. These recognitions celebrate the culture our teams have built—collaborative, supportive, and committed to people-first leadership. (Full announcement: RedCloud Named a Best Place to Work in the Consulting Industry ) Looking Ahead to 2026 As 2025 roared with significant expansion, we're setting our sights on 2026 as the year we truly accelerate. RedCloud is incredibly well-positioned to make an even greater impact, fueled by our expanding global footprint, our richer, more diverse client portfolio, and a team whose brilliance we celebrate daily. To our incredible consultants, our valued clients, our vital partners, and our community: a heartfelt thank you. Your unwavering dedication, your innovative spirit, and your sheer passion are the very heartbeat of RedCloud's success and made this a truly landmark year we'll never forget. Here’s to another year of growth, opportunity, and meaningful work with our clients and in our communities!

Meet Nate, the mind behind RedCloud’s Power Platform and Agentic AI practice. He’s focused on helping organizations unlock automation, analytics, and AI with everyday tools like Power BI, Copilot, and Azure — always looking for ways to put problem‑solving power directly in the hands of users. From his first big project with Microsoft to his latest experiments deploying AI agents on his own desktop, Nate’s journey has been full of surprising pivots and discoveries. In this 10Min With, you’ll get a glimpse into what drives him, what he’s building next, and a few unexpected passions outside of work. Describe your role and what you do in a nutshell   I am leading our Power Platform and Agentic AI practice, helping organizations leverage Microsoft technologies like Power BI, Power Platform, Copilot, and Azure to drive automation, application development, analytics, and AI. Essentially, I am always looking for ways for everyday users in organizations can tackle their own business problems.     What do you aim to accomplish professionally this year?   Launch a successful AI practice with a strong portfolio of real-world use cases.  Build expertise in Agentic AI and integrate it into client solutions.  Develop repeatable frameworks for AI strategy and governance.    What are you most proud of in your career so far?   My first major Power Platform project involved helping Microsoft localize marketing content for Office, Azure, Xbox, and Windows. Previously, I was a traditional tech PM focused on specs, plans, and risks. This project showed me how easily large-scale automation could be set up with minimal technical skills, inspiring me to become a Citizen Developer, and it was definitely a pivotal moment in my career.    Tell us about something interesting you've learned recently.   My friends are for sure sick of me talking about Agents and AI. But you are reading this, so recently I just learned how to deploy my own LLM model on my Machine, use AI to build a much better-looking version of Copilot/ChatGPT, and connect it to an automation orchestrator. I know technical terms. Basically, on my personal desktop, I have a free AI agent and can actually do more than stuff with text. It is still probably too technical for some, but I was shocked at how easy it was to set up.    If you could suggest a book for the entire team to read, what would it be and why?   I am not a book reader; the last book I read was in 2011. Instead, I watch lots of nerdy YouTube videos and read all sorts of forums/blogs on the internet. For example, my favorite YouTube channel is one called SmarterEveryDay. How Destin can explain all sorts of things is the best.    What's a piece of obsolete technology you still have a soft spot for?   Nokia 3000 series. It takes me back to the days when Snake and limited text messaging were the only distractions on my phone.    What's one thing people don't know about you that they would be surprised to discover?   When I mention the number of countries I have visited, which exceeds 40, it often elicits surprise from others.    What are you passionate about or enjoy outside of work?   Music is an understatement here. I listen to over a hundred hours of music a month (Actually, on average 120 hours, I know this cause, of course, I use Power Platform to track this), have been to hundreds and hundreds of shows, performed at shows, and produced music. Additionally, I am a fan of American football, smart home tech, and video games.

Each year, we’re honored to shine a light on an incredible student who embodies leadership, compassion, and a commitment to making a difference. This year, we’re thrilled to announce that Lucy Naiman, a senior at Sehome High School, has been selected as the 2025 RedCloud Consulting and Toys for Kids Seattle Scholarship Recipient. Now in its eighth year, this scholarship reflects RedCloud’s ongoing commitment to supporting the next generation of leaders who lift up their communities. Lucy is the definition of the spirit RedCloud looks for! A 4.0 GPA student and dedicated community volunteer, she has spent more than 150 hours serving as a juror and attorney in Teen Court — a peer-led program that gives young people the opportunity to take accountability, rebuild trust, and change their futures. “I had made a difference! Simply by speaking on behalf of my peer.” — Lucy Naiman Lucy’s story began nervously — hands shaking in front of a judge and jury — and grew into a powerful calling to advocate for others. Today, Lucy speaks with confidence, purpose, and compassion. “Speaking up fills me with joy, not anxiety, as I am able to give back to my community and give a voice to my peers.” Her mentors describe her as “compassionate, confident, and determined to lead with empathy.” Lucy hopes to continue her education with the goal of becoming a lawyer, turning her passion for advocacy into a career of service. “Each year, this scholarship reminds us why we do this work — to invest in our region’s most important resource, young people, who inspire us with their courage, leadership, and heart,” said Brett Alston, RedCloud Managing Partner and Toys for Kids Seattle Board Member. “Lucy represents everything this scholarship stands for, and we’re so proud to support her journey.” Through our partnership with Toys for Kids Seattle, RedCloud has proudly awarded scholarships to outstanding students for eight years running. These young leaders remind us that investing in education is one of the most meaningful ways we can give back. Read about our past scholarship recipients: 2024 Scholarship Winner  2023 Scholarship Winner  2022 Scholarship Winner  Congratulations, Lucy. We can’t wait to see all that you will accomplish — and the lives you’ll touch along the way.

At the recent Power Platform Conference in Las Vegas, Microsoft didn’t just preview new features. They signaled a seismic shift. Low-code is no longer the future — AI-generated code is. For years, low-code platforms promised simplicity and accessibility. That promise has evolved. Today, app creation is no longer about dragging and dropping. It’s about prompting and generating. AI is now the engine behind every modern Power Platform experience. The New Spectrum of App Creation App development now spans a continuum. On one end, fully AI-generated experiences. On the other hand, pro-code environments accelerated by AI. In between, hybrid tools that blend prompt-driven creation with manual flexibility. Here’s how the current Power Platform lineup maps to this new reality: Tool Status Experience App Type Data Access Coding Flexibility App Builder Frontier Program Single Page Copilot-Driven SharePoint Only No Code Editing Gen Pages GA Single Page Dataverse Apps Dataverse/SharePoint/SQL/Some Azure Limited Code Editing Code Agent Early Access Multipage Code App Dataverse Limited Code Editing Code Apps Preview Multipage Code App All Connectors Full Code Editing These tools aren’t just upgrades. They’re a redefinition of how apps are built. React is now the default architecture. Whether you’re creating a simple form or a complex enterprise solution, the code is AI-generated, React-native, and ready for scale. Agents Are the New Builders Microsoft’s agent ecosystem is reshaping development: Insight Agents:  Summarize dashboards, explain trends, and generate briefings from live data in tools like Power BI. Workflow Agent: Set up flows with simple prompts. Define instructions, actions, and connections in seconds. Productivity Copilots:  Draft content, interpret documents, and suggest actions inside Microsoft 365, Power Platform, and Dynamics. Governance & Evaluation Agents:  Ensure quality and compliance by checking accuracy, safety, and reliability, while surfacing oversight metrics. Autonomous & Self-Hosted Agents : Run on self-managed infrastructure using open-source models for full control over cost and privacy. These agents don’t just assist. They co-create. They interpret intent, generate code, and optimize logic in real time. Copilot Pricing: Credits Over Messages Copilot is shifting to a credit-based pricing model. Features within the studio now carry associated credit costs. For some, this will create challenges in accurately estimating project costs and usage. Microsoft encourages makers to use the Estimator, go here to view, to plan, and help understand spending for each agent.  Real-World Demos: From NASA to Network Ops The conference showcased stunning use cases: A solar system map tracking NASA missions via Gen Pages A nationwide outage dashboard for Lumen built with Code Agent These weren’t just prototypes. They were proof that AI-generated code can handle real complexity, scale, and performance. What This Means for RedCloud RedCloud thrives on anticipating what’s next. This is one of those moments. The future of app development is no longer low-code. It’s AI-generated, React-native, and agent-powered. For clients, this means faster delivery, smarter automation, and scalable architecture. For RedCloud, it’s a chance to lead the charge — architecting solutions that blend human creativity with machine precision. Low-code is dead. The future is already here. Ready to build smarter? Contact RedCloud’s Data & AI practice  to learn how we can help you harness AI-generated development, build and deploy Agents, optimize your Power Platform strategy, and future-proof your digital ecosystem.

After months of work, we are excited to introduce RedCloud’s “ChangeFlow”—a big step forward in how transformation offices operate. ChangeFlow is not just a new tool; it’s a game-changing capability designed to help organizations work smarter, faster, and with greater impact. The Journey: From Idea to Launch Our goal for ChangeFlow was clear: help transformation leaders move past scattered efforts and become true orchestrators of enterprise-wide change. We set out to tackle common roadblocks — siloed data, disparate delivery processes, overlapping projects, and limited insight into how initiatives connect and impact the business. Through real-world testing and feedback, we’ve shaped ChangeFlow into a solution that unifies change and impact assessments, stakeholder mapping, and operations in partnership with dynamic dashboarding to deliver a seamless experience. ChangeFlow is more than a platform. It is a new way of working that will elevate your team to become strategic partners for the enterprise. What This Tool Does ChangeFlow helps teams: Break down silos  by identifying where portfolios, programs, and projects overlap or compete, enabling leaders to make more informed decisions and avoid unidentified change collisions (Or at least proceed with eyes wide open). Support strategic conversations  by providing a clear view of the enterprise change horizon, enabling teams to adjust timelines and avoid conflicts, and partnering with P-andV-MOs and leaders to orchestrate change and avoid accidental stacking. Simultaneously Empower RedCloud Clients and consultants  to deliver programs smoothly by building cross-initiative transparency without building an environment where change managers compete for long-term stakeholder attention, or where clients are expected to trust consultants blindly with little visibility into their work. ChangeFlow solves for both. Speed up execution  by leveraging AI in early change assessments, eliminating manual busywork, allowing change-makers to focus on what matters most: Enabling the kinds of engagement that ensure business confidence through change remains high.  The results so far are promising. Bottlenecks are identified, and programs are being combined. Our partners are elevating the conversation while we continue to deliver excellence in change programming. Initiative overlaps and stakeholder impacts are clearer than ever. Real-time data is driving better planning and forecasting. Increasingly targeted, AI-enabled communications have helped users cut through the noise. Leaders have greater clarity about where they need to be, which project, and which teams they support. This isn’t just about efficiency; it’s about elevation. It is about helping transformation teams step up as trusted advisors who can confidently navigate complexity and lead change. What This Unlocks for You ChangeFlow isn’t just a smarter way to manage change — it’s a strategic lever for transformation leaders ready to lead with foresight. With automation and AI woven into the fabric of operations, you can: Surface hidden intersections across initiatives before they become bottlenecks. Reframe scattered efforts into unified programs that drive enterprise value. Navigate the change horizon with clarity, earning trust and buy-in from sponsors and delivery offices.  Step into a new role — not just managing change, but orchestrating it with precision, influence, and insight. Looking Ahead The launch of ChangeFlow is just the beginning. Our vision is to make transformation offices the central hub connecting departments, project teams, and leadership across the organization. With a shared view of impact and priorities, teams won’t compete blindly — they’ll coordinate smarter. We also plan to leverage AI agents to drive earlier insights and faster turns for assessments, planning, and development of change-related deliverables.  In short, ChangeFlow gives transformation leaders the insights, tools, and influence to shape the future with clarity, confidence, and cohesion.

At RedCloud, we understand that the interview process can sometimes feel overwhelming. That’s why our dedicated recruiting team is here to offer expert advice to help you navigate it with confidence. Drawing from our experience, we’ve compiled essential tips to set you up for success. Depending on the opportunity, your Recruiter may schedule one or more of the following interview types: Behavioral Interviews – Typically a 30-minute conversation with a RedCloud Account Manager who will assess your professional demeanor, communication style, and overall culture fit with our firm. Case Studies or Technical Interviews – These are usually 30–45-minute sessions with a RedCloud Account Manager where you’ll walk through a real-world scenario or technical challenge. We use these discussions to understand how you think, problem-solve, and approach client situations. Client Interviews – While not always required, these interviews can vary in duration and format, as each client has their own unique process and style. Your RedCloud Recruiter will ensure you’re fully prepared with all the details ahead of time. Before Your Interview Most interviews are conducted via video through Microsoft Teams. Please join the meeting five minutes before the scheduled start time. You can ask your RedCloud Recruiter to help test your Teams setup to ensure your video and audio are working properly. Choose a background that reflects professionalism. Make sure your space is clean, quiet, and organized. Prepare in advance to minimize distractions (such as pets, children, or background noise) during your call. If you’re using Teams on your desktop, consider selecting a RedCloud backdrop image from our gallery below for your background. Alternatively, you can blur your background for added focus. Dress professionally, as you would for an in-person interview. Please remove hats and sunglasses before joining the call. Avoid graphic t-shirts or clothing that could be interpreted as political or polarizing. Research your interviewer, the team, and the organization. Come prepared with thoughtful questions that demonstrate your interest and help you learn more about the role’s day-to-day responsibilities, deliverables, and team culture. Your RedCloud Recruiter will provide as much insight into the team and scope as possible, but if you have questions beforehand, please don’t hesitate to ask. During Your Interview Be yourself. We value authentic communication and want to hear your personal experiences and insights. Please avoid using AI tools or scripted responses during your interview, as we’re looking to understand your natural communication style and how you approach problem-solving. Use of AI tools during the interview may disqualify you from further consideration. Have your resume handy and be prepared to discuss your prior work experience in detail. Most interviewers prefer clear and concise answers. When responding to questions, consider this framework: The scope or challenge Your specific contribution The end impact or result Be respectful of your interviewer’s time. Provide complete responses but avoid going off on tangents. Pause occasionally to give your interviewer the opportunity to ask follow-up questions. Please do not discuss decision timelines or compensation details with the client interviewer. These topics should be addressed with your RedCloud Recruiter or Account Manager. After Your Interview When your interview wraps up, please let your recruiter know how it went. We’d love to hear your thoughts! Teams Backdrops If you’d like to use one of the RedCloud-branded backdrops for Teams featured below. Right-click on the image, select “Save As”, and save it to your preferred location before uploading it to your Teams app. Good luck! We’re rooting for you!

How to achieve enterprise-level capabilities with Self-Hosted Agentic AI This is the final post in our series on AI adoption. In Part 1, we examined how large enterprises have broken the traditional technology adoption curve, outpacing small businesses in AI deployment through substantial resource investments—deep talent pools, complex infrastructure, and organizational capabilities that small businesses struggle to match. Part 2 explored how autonomous architecture—systems that manage, optimize, and evolve themselves—could level this playing field and return the competitive advantage to smaller, more agile organizations. The critical question that remains is: Can small businesses actually access enterprise-level AI capabilities without enterprise-level budgets? Let’s Talk Technology Rather than relying on external AI service providers like OpenAI or Anthropic, a self-hosted Agentic AI model runs on your local device, managing the data on your own hardware, and maintaining full control over the entire technology stack. The reason self-hosting is best suited for autonomous architecture is to forgo all the recurring per-use costs and to keep your data contained within your environment. Why is this approach now viable? Just 18 months ago, this type of infrastructure would’ve required specialized vendors and six-figure budgets. Now, the same can be accomplished with open-source tools and some modest hardware. Here’s how we’ve done it. The Autonomous Architecture Stack Our solution requires three core components working together: The Orchestration Layer: n8n workflow automation, and a custom MCP Server n8n is a free open-source workflow automation platform that provides visual workflow design, system integration, and event-driven execution. Think of it as the nervous system—coordinating actions across different tools and systems, routing information, and managing complex multi-step processes. A custom MCP (Model Context Protocol) server extends n8n's capabilities by enabling AI agents to interact with its workflows dynamically. Instead of predefined automation paths, the MCP server allows agents to query available actions, execute workflows based on reasoning, and adapt behavior based on results. This is what transforms static automation into autonomous architecture. It is capable of managing itself. The AI Model Layer: Ollama and GPT-OSS Ollama provides a simple interface for running open-source language models locally, without external API calls. GPT-OSS — OpenAI's open-source release of advanced reasoning techniques — is our chosen open-source language model used for handling more sophisticated autonomous decision-making. These models power the reasoning and decision-making of your Agent. They interpret user requests, analyze data, generate responses, and make judgment calls about workflow execution. As mentioned, running these locally eliminates the per-token costs and keeps your sensitive data on-premises. These modern open-source models perform well enough for most business applications (e.g., customer support, document processing, data analysis, workflow automation), though they may not match Chat GPT-5 on every benchmark. Integration & Deployment: Docker and Web UI Docker containerizes each component, making deployment consistent and updates straightforward. The entire solution’s stack runs in containers that can move between development machines, production servers, or cloud infrastructure if needed. Web interfaces make the system accessible. Our workflows and models are configured through n8n's visual interface. We can monitor operations and adjust behavior, as needed, without writing any code. Code-level customization is still available though, should we desire it. An enterprise AI platform would typically require a dedicated DevOps team for this kind of deployment and maintenance. Our solution reduces this configuration management to a single individual. Bringing It Online You can implement a solution similar to ours using this 4-step process: Step 1: Deploy the core infrastructure Install Docker on your chosen hardware—this could be a dedicated server, a capable workstation, or a virtual machine. Deploy n8n in a container. Add Ollama with your chosen language models. Set up the custom MCP server to bridge n8n and your AI models. At this stage, you're not building production automation yet. The goal is a working environment where you can experiment with workflows and model interactions. Recommended Hardware: A modern workstation with 16-32GB RAM and a decent CPU can handle this workload. Time investment: 40-60 hours for someone with technical aptitude but no prior experience with these tools. Halve that if you have previous container and automation experience. Step 2: Your first Autonomous capability Implement one well-defined autonomous workflow. Good candidates for this might include: Customer inquiry routing and initial response Document processing and data extraction Routine workflow automation with decision points System monitoring and basic self-healing The key is choosing something with clear value, manageable scope, and tolerance for iteration. You're learning how the system behaves in production while delivering a measurable benefit. Here’s an example: Let’s say your customers contact you via email or chat. Your n8n autonomous workflow can receive them, pass content to your local AI model for classification and initial response generation. The AI model analyzes intent, checks relevant customer history from your CRM (API integration required), drafts a response, and either sends it automatically or routes to a human for approval. The system logs all the interactions for use in quality monitoring and continuous improvement. Step 3: Data mining & refining Monitor your workflow’s performance. Track accuracy, response quality, error rates, and edge cases. Adjust prompts, refine the workflow, and improve integration handling based on your actual usage. This step is for building confidence in your autonomous systems and helps to develop an intuition about what works. Your direction is instrumental in informing what will become the autonomous architecture’s ability to optimize & evolve itself. Step 4: Start to scale Add new capabilities systematically. Each new autonomous workflow builds up infrastructure and knowledge from previous implementations. The marginal cost of additional automation drops significantly once a foundation exists. Strategic Advantages Beyond the cost savings and data security benefits we’ve mentioned, self-hosted Agentic AI provides some other competitive advantages: Operational Leverage: Self-healing capabilities and automated workflows reduce maintenance costs and emergency responses. Rapid Iteration: Without vendor approval processes or API rate limits, you can experiment freely. Test new workflows, adjust agent behavior, and optimize performance on your timeline, not a vendor's roadmap. Customization Depth: Full control over models and workflows enables domain-specific optimization that cloud services can't match. Fine-tune your models on your specific use cases. Build integrations for proprietary systems. Optimize for your exact requirements. The Competitive Inflection Point In this series, we have traced a potential reversal in AI adoption patterns. Part 1 showed how resource intensity gave large enterprises the AI adoption advantage. Part 2 identified autonomous architecture—self-managing, self-optimizing systems—as the technology shift that could return competitive advantage back to small businesses and startups. In Part 3, we have demonstrated how self-hosted Agentic AI can make autonomous architecture accessible at a cost that small businesses can afford. A self-hosted Agentic AI solution changes the competitive equation. As a small business or startup, you can deploy autonomous systems that manage themselves, adapt to changing conditions, and operate at scale—with budgets measured in thousands rather than hundreds of thousands of dollars. As we’ve shown, the technology is cheap, and it is ready. The time to seize on this advantage is now, before a wave of acquisitions puts these cheap and easy AI services behind a barrier of premium licenses within enterprise suite applications. RedCloud Can Help If you’re ready to explore autonomous architecture, we can partner with you in a number of ways: Identify opportunities: Look for one process where autonomous capabilities would create clear, measurable value, and do a wholesale redesign of your work around it. Build the capability: Someone needs to understand these systems and train your technical staff on the initial setup and knowledge needed to expand and scale. Experiment with intent: Deploying your first autonomous capability will require you to learn and iterate. A strong foundation for your AI models will have a compounding benefit over time. Measuring impact: Establish the metrics to track the impact on your business. This data will guide your scaling decisions. The autonomous architecture shift is just beginning, and true to the traditional technology adoption curve, small businesses who recognize this inflection point and act as the early adopters have a tremendous opportunity. The opportunity to realize the productivity gains from successful AI deployments that will enable them to operate with fundamentally different economics and agility than their larger competitors. Contact us  today, and our experts will partner with you as you navigate this profound step forward in AI adoption.

Adoption of AI models has broken the traditional technology adoption cycle Artificial intelligence isn’t just another technology wave. It’s a fundamental shift in how businesses operate, compete, and grow. Unlike past innovation cycles, AI adoption has upended expectations. Enterprises are leading the charge, startups are scrambling to catch up, and every organization faces critical choices about cost, control, and capability. At RedCloud, we believe success in this era depends on cutting through the hype and building practical, future-ready strategies. This three-part blog series offers a perspective on AI adoption, including a look ahead to the next frontier—natural code, and a playbook for building agentic AI on your own terms. Along the way, we’ll highlight how RedCloud’s AI services help clients to unlock the potential of big data, gain valuable insights, automate processes, and accelerate transformation. Why Large Enterprises Are Leading the Charge For decades, the   technology adoption curve  followed a predictable pattern: scrappy startups and nimble small businesses would embrace new innovations first, while large enterprises lagged behind, weighed down by bureaucracy, legacy systems, and risk aversion. From personal computers to cloud computing, from social media to mobile-first platforms, the story was always the same—small businesses led, and large enterprises followed. But, so far, artificial intelligence is rewriting this narrative entirely. The Great Reversal Today's data reveals a striking paradox: when it comes to AI adoption, large enterprises are not just keeping pace with small businesses—they're leading the way. According to June 2025 transaction data in   Ramp’s AI Index , only 37% of small businesses have deployed AI in some form, compared to 49% of large enterprises. Looking a level deeper, a   2024 study by Boston Consulting Group  revealed only 26% of companies have developed the necessary capabilities to move beyond AI proofs of concept and generate tangible value, and they are predominantly large enterprises.  The AI adoption patterns we’ll discuss in this post may represent more than just a temporary market dynamic; it could be a signal of a permanent shift in how innovative new technologies proliferate throughout the world economy. Because AI offers such transformative potential, it seems the large enterprises that have pulled ahead of the pack are likely to stay there. According to   MIT’s Sloan School of Management , organizations in the first two stages of their AI maturity had financial performance below their industry’s average, while organizations in the last two maturity stages performed above their industry’s average. The result is a vicious cycle, where large enterprises that can afford to invest heavily in AI capabilities are creating distance from their small business competitors, which in turn enables them to only further increase that disparity over time. There are signs that small businesses are fighting to catch up.   According to Goldman Sachs , small business AI adoption has jumped to 17% from where it was two years ago. What this fails to capture, however, is that this growth is masking a crucial gap in the sophistication and maturity of implementation for AI solutions. Stated plainly, large enterprises are getting more from AI solutions because they can invest more and scale the value from their solutions further. The Resource Reality The primary driver of this technological reversal lies in the fundamental nature of AI adoption itself. Unlike previous technologies that could be implemented incrementally with modest investment, successful AI deployments have required substantial upfront resources and organizational capabilities. In practice, this means that large enterprises have had a natural advantage in building and implementing AI Solutions. They’ve invested in centralized AI governance models, established centers of excellence for risk and compliance, and created hybrid organizational structures that balance centralized oversight with distributed implementation across their business units. Smaller businesses simply lack the organizational complexity to support such sophisticated deployment efforts. We’ve also seen large corporations fiercely competing for people with AI skills.   Research from IBM  shows that 33% of companies cite limited AI skills and expertise as the top barrier to successful AI adoption. Large enterprises can afford to hire teams of AI specialists, data scientists, and implementation managers, whereas smaller businesses often rely on as few as one qualified professional or a handful of self-taught employees to guide their AI adoption journey. So, large enterprises have a superior infrastructure and a deeper talent pool to draw from.  What has been the result? The Implementation Maturity Gap Beyond raw resources, large enterprises are demonstrating superior strategic sophistication in their AI adoption approaches. The data shows clear differences taken by companies of different sizes. Asana’s report on the State of AI at Work 2025  finds "there’s a widening gap between the 29% of organizations we call AI Scalers and everyone else. AI Scalers don’t just “try AI.” They redesign work around it—and see a 91% productivity boost.". Further, less than one-third of companies report following most of the   12 key AI adoption and scaling best practices identified by McKinsey . Within that, however, large enterprises consistently outperform small businesses across these practices, including establishing dedicated AI teams, creating internal communications about AI value, and embedding AI solutions into business processes effectively. So, we’re seeing large enterprises focus on AI Solutions that affect their core business processes, rather than just experimenting with support functions, and putting the practices in place that are necessary to be successful. They identify and prioritize their most impactful use cases for AI transformation, whereas small businesses often scatter their limited resources across various experiments with AI solutions.  The Challenge for Small Businesses If you’re part of a small business or a startup, what can you do about this? You have good reason to be skeptical that you stand a chance of catching up and reclaiming your role as the innovators/early adopters. According to Goldman Sachs , about 42% of small businesses say they still don't have access to the resources and expertise necessary to successfully deploy AI. Of those businesses, 60% cite a lack of expertise in applying AI to their specific business context. So, it’s not just about hiring AI specialists; it's about understanding how to transform existing business processes effectively using AI solutions. As AI becomes increasingly more essential, the traditional startup advantage of speed and agility appears to have been neutralized by AI's complexity and resource requirements. Unlike deploying a mobile app or setting up a social media presence, implementing AI effectively seems to fundamentally favor large enterprises. The Generative AI Exception One notable exception to this trend is generative AI adoption, where small businesses have shown stronger initial adoption in certain areas. A   2024 survey from BizBuySell  showed that over 75% of respondents reported they use AI tools for Marketing functions. The reason is simple: AI excels at tasks like content creation, copywriting, social media management, email marketing, and analytics, and the tools available for performing these tasks can be used cheaply and immediately without an extensive technical infrastructure. Will we see more examples like this in the future?  Or perhaps we’ll see a wave of acquisitions of these cheap and easy AI services, putting them behind a barrier of premium licenses within enterprise suite applications? Don’t Give Up Yet The AI revolution has been fundamentally different from previous technology cycles in its initial phases. While the internet and mobile computing democratized access to powerful tools, AI has thus far consolidated its advantage among those with the resources to implement it effectively. Being a large enterprise hasn't been a disadvantage in AI adoption; it's been a prerequisite for early leadership. However, just as the internet eventually became accessible to garage startups, and mobile apps empowered individual developers to compete with established software giants, AI solutions may soon be approaching their own democratization inflection point. Coming in Part 2 The current corporate dominance in AI adoption has profound implications for entrepreneurship, competition, and economic opportunity for all of us. In Part 2 of this series , we’ll provide our point of view about how the pendulum may swing back in favor of the nimble innovators who have historically been the drivers of technological disruption. Small businesses and startups, it turns out, do have an opportunity to reclaim their traditional role as technology pioneers.