Your AI Initiative Stalled. We Fix That.
You bought Copilot and nobody uses it. You hired a consultant who delivered a 90-page deck and zero working code. Your team thinks AI is either a threat to their jobs or a toy that hallucinates. Sound familiar?
We fix broken AI programs. Production systems in 2 weeks. Measurable ROI. Real engineers, not slide-deck salespeople. Get a free quote—20-minute call, no obligation.
The Numbers Are Brutal
This is not opinion. This is what the research says about AI projects right now.
of AI projects fail to deliver expected value or move beyond pilot
of Microsoft 365 users who access Copilot Chat actually pay for it
of successful AI pilots fail when scaling to production
average cost of a failed AI project including opportunity costs
Sources: Pertama Partners AI Failure Statistics 2026, Microsoft Q2 FY2026 earnings, IBM CEO Study 2025, Fortune/MIT GenAI Pilot Study 2024.
Why AI Projects Actually Fail
It is almost never the technology. 84% of AI failures are leadership and strategy failures. Here are the real reasons your AI initiative stalled—and what to do about each one.
You bought Copilot and nobody uses it
Microsoft reports only 3.3% of Copilot Chat users convert to paid. When workers have a choice between Copilot, ChatGPT, and Gemini, only 8% choose Copilot. The product has persistent negative accuracy satisfaction scores (−19.8 NPS) and brand confusion across five different “Copilot” products. Enterprise deployments stall for months over data governance issues—over 15% of business-critical files are at risk due to permission problems. Some enterprises use only 10% of purchased seats.
The fix: Stop buying licenses and hoping for adoption. You need a model-agnostic approach that selects the right tool for each job—Claude for analysis, GPT for generation, open-source for on-prem, fine-tuned models for your domain. One-size-fits-all doesn't work. We help you pick, deploy, and train your team on what actually fits.
You hired a consultant who delivered slides, not software
The classic: $40,000 strategy retainer, 90-page PowerPoint, six-month “AI readiness assessment,” and zero lines of working code. The person leading the engagement has never deployed a production agent, connected a model to real data, or owned an outage. They came from marketing. Or “blockchain.” Their LinkedIn says “CEO” of an “AI company” they founded six months ago. They talk about AI on LinkedIn constantly, yet they have not built anything.
The fix: Ask what they have shipped. Ask for production URLs. Ask who on their team has owned an outage. We wrote the definitive piece on this.
Your team doesn't trust AI—or fears it
Pew Research (2025) found that US workers are more worried than hopeful about AI in the workplace. 90% of workers use AI tools, but 75% abandon them mid-task due to accuracy concerns. 45% don't trust colleagues' work when AI was involved. 36% prefer colleagues avoid AI entirely. Entry-level workers are the most anxious—they think it replaces them. Senior staff think it's “cheating.” Nearly half of employers don't pay for AI tools or provide meaningful training.
The fix: You cannot mandate adoption. You have to demonstrate value in their actual workflow, on their actual problems. Our “Asking AI To Do Things With Our Data” framework takes 30 minutes and creates shared understanding without condescension. Then we build on their real pain points—not theoretical use cases from a vendor deck.
Your pilots never make it to production
73% of successful AI pilots fail when scaling to production. The weekend prototype your team built is impressive in a demo but collapses under real load, real data, and real edge cases. Government contractors build “accelerators” that cannot survive a security review. The gap between “it works on my laptop” and “it runs in production” is where most AI initiatives die.
The fix: We build production-grade from day one. No throwaway prototypes. Every sprint deliverable is code that can ship. We deployed a production agent in 2 weeks that saved $10K+ per month.
The wrong people got promoted because they talked about ChatGPT first
Organizations panicked and handed AI leadership to whoever raised their hand first—often the person most comfortable with LinkedIn posts, not production systems. Now you have an “AI lead” who cannot explain the difference between an embedding and an API call, a team of yes-people arbitrarily checking boxes, and a roadmap that looks impressive but delivers nothing. Agile got replaced by theater. Product management got replaced by demo day presentations of features nobody asked for.
The fix: You need an external team with no internal politics and no incentive to protect a bad decision. We follow real agile, real product management, and lean iteration. We surface the highest-impact problems first with our Lightning Decision Jam process, then build directly against them. Every two weeks you see working software—not a status report.
You don't understand the difference between “agent” and “agentic”
An agent is a single AI system that perceives, reasons, and acts: it takes a goal, breaks it into steps, uses tools, and iterates until done. Agentic AI is the infrastructure layer—the orchestration, state management, tool integration, and coordination that lets agents operate effectively. The real power comes from multi-agent orchestration: specialized agents collaborating on complex tasks, with supervisor loops catching errors and manager agents routing work. Gartner predicts 40% of enterprise apps will feature task-specific agents by 2026, scaling to full multi-agent ecosystems by 2029.
The fix: You need a team that builds these systems, not one that explains them on a whiteboard. We have dozens of live agents you can try right now. We are your local LangChain experts and have been building multi-agent systems since 2023.
Your website is not cutting it anymore
SaaS is getting disrupted. AI agents are eating software from the inside. Microsoft's own leadership has said traditional business SaaS apps are “on their way out.” AI-native companies average $3.48M revenue per employee—10–20x more efficient than traditional SaaS. Our CEO replaces a SaaS tool he's sick of paying for every week with custom, owned code. Your website should have AI agents embedded—fielding leads, qualifying prospects, answering questions, getting you recommended by ChatGPT and Gemini.
The fix: We build agentic websites—modern, fast, with embedded AI agents that convert visitors and get you found by AI search. We do it for ourselves and our clients. No WordPress. No templates. Production code you own.
Your prompts are lazy and your tool selection is worse
Good AI systems require good prompts, good models, and good goal setting. You cannot get lazy with any of it. A bad prompt in the wrong model with a vague goal produces hallucinating garbage. Prompt engineering is a real discipline—how you frame instructions, how you structure context, how you handle edge cases. Model selection matters: Claude thinks differently than GPT, open-source models have different strengths, and the right choice depends on your data, compliance, and budget. You need model-agnostic expertise, not vendor loyalty.
The fix: We bring prompt engineering, model selection, and goal-setting rigor to every engagement. We are not loyal to any vendor—we pick what works. And we show you how to evaluate it yourself so you are never dependent on us.
Before You Hire an “AI Expert,” Ask These Questions
What Gartner Says Is Actually Coming
The hype cycle is real, but the underlying shift is too. The companies that win will be the ones that build with practitioners now—before the “Trough of Disillusionment” becomes a budget freeze.
40% of enterprise apps will feature AI agents by 2026
Up from less than 5% in 2025. By 2028, 15% of day-to-day work decisions will be made autonomously by AI agents. By 2035, agentic AI is projected to drive $450B+ in enterprise software revenue. The window to build your strategy is now.
Multi-agent systems are a top-10 strategic trend for 2026
Not single chatbots—systems of specialized agents collaborating. Manager agents routing work, supervisor agents catching errors, specialist agents handling domain tasks. This requires real orchestration expertise, not a ChatGPT wrapper.
Model-agnostic is not optional
No single model dominates every task. Claude excels at reasoning and analysis. GPT at generation and creativity. Open-source models win on cost and privacy. The right strategy uses multiple models for different jobs—not one vendor lock-in.
CIOs have a 3–6 month window
Gartner warns that organizations who don't define their agentic AI strategy in the next 3–6 months risk falling significantly behind competitors. Waiting is a strategy—but it's the losing one.
(Most) SaaS Is Dying
“Every week I take a tool I'm sick of paying for and replace it with something custom in-house. I own all my code. I can make any customizations. I can talk to my AI developers any time of day. There's a reason the market took a tumble. Most SaaS is dying.”
AI agents are eating SaaS from the inside. When your primary interface becomes an agent, SaaS products that were “the place work happens” become back-end utilities priced like commodities. Per-seat pricing, human-centric interfaces, and brand differentiation all become liabilities when machines orchestrate workflows.
AI-native companies already average $3.48M revenue per employee—10–20x more efficient than traditional SaaS companies. The disruption is not theoretical. It is happening now.
How We Fix Stalled AI Programs
We do not do discovery phases, onboarding periods, or six-month roadmaps that delay building. We start working on day one.
20-Minute Call
We show up prepared with research on your business. You tell us what stalled and where it hurts. If there's a fit, you get a tailored proposal at no cost.
Lightning Decision Jam
2–3 hour structured session. Your team's scattered problems become a prioritized, actionable backlog. Sprint zero is defined before you leave the room.
Working Software in 2 Weeks
Demo day. Not slides. Not wireframes. Working software that solves a real problem and saves real money. Then we do it again. Every two weeks.
What you get for less than one full-time hire
Stop Paying for AI Theater. Start Shipping.
Talk to our CEO or a senior account manager for 20 minutes. We show up prepared. If there's a fit, you get a tailored proposal at no cost. Most clients start small and scale from there.
The quote is good for a year. We have no interest in pressuring a timeline.
or call us at (443) 214-3143
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