AI Strategy & Intelligent Operations.
Identify the AI use cases that matter. Deploy the agents that earn their place. Measure what actually changes.
What we keep seeing.
Most enterprise AI initiatives stall after proof-of-concept. The capability is there, the licenses are paid for, the demos look convincing, and yet six months later, operator workflows have not changed, and the board is still asking when the ROI lands.
The gap is rarely the model. It is the strategy underneath. Tool-led approaches start with what was bought and hunt for use cases that might justify it. The discipline runs the other direction, use cases first, agents second, tools last.
Our approach.
We start with use cases, not tools. Listen, we interview operators and surface the moments where AI would actually compound their work. Diagnose, we map feasibility, data readiness, and governance gaps. Design, we specify intelligent agents and automation flows that sit inside workflows the team already uses. Deliver, we build, evaluate, deploy, and measure.
We are tool-agnostic. Microsoft Copilot, Anthropic Claude, OpenAI, custom-trained models, open-source agent frameworks, we recommend what fits your data, your security profile, and your operators. We will tell you when AI is the wrong answer.
Every engagement ships with an evaluation harness, automated tests for accuracy, hallucination rate, and edge-case behaviour. AI without evals is hope; AI with evals is engineering.
What the data shows.
Outcomes are best understood against the broader landscape. Below, published benchmarks from independent research that frame this engagement type.
-
30%
Of generative-AI projects will be abandoned after proof-of-concept by end of 2025, driven by poor data, inadequate governance, and unclear business value.
— Gartner, July 2024 -
72%
Of organizations now use AI in at least one business function, up from 55% the prior year. Adoption is no longer the question; durable value is.
— McKinsey, "The State of AI in Early 2024" -
26%
Of companies have developed the capabilities to move beyond AI proofs-of-concept and actually generate value at scale. The remaining majority stall.
— BCG, "Where's the Value in AI?", October 2024
Capability, not headline.
We list these because you'll ask. We list them last because they're the means, not the engagement.
- Microsoft Copilot, Microsoft 365 · Copilot Studio · Power Platform integration
- Anthropic Claude, Sonnet · Opus · Claude Agent SDK
- OpenAI, GPT-4o · Assistants API · custom GPTs
- Open-source agent frameworks, LangGraph · CrewAI · n8n
- Vector & retrieval, Pinecone · Weaviate · pgvector · Azure AI Search
- Evaluation & governance, eval harnesses · prompt registries · audit logs
- Custom-trained models, fine-tuning on your data when off-the-shelf doesn't fit