AI Solutions
AI that works with your data, not around it.
Most AI projects stall somewhere after the demo. We start from the systems and the data you already run, so what gets built survives contact with your business.
Book a Discovery CallRAG system
Claude
Idle
Document
processing
Indexed
Raw documents
Assistant
connected to your dataWhy AI projects fail
AI is only as good as the data underneath. Most projects fail not because of the model — but because the data is inconsistent, incomplete, or unstructured.
Demos built on curated sample data don't survive contact with real business data. Without a production plan from day one, the POC is where the project ends.
SaaS AI tools charge per seat, per query, or per document — and your data flows through their servers. Costs scale unpredictably and data governance becomes a concern.
What we build
We scope to a specific, measurable problem — not the most comprehensive solution.
We build semantic search systems that let your team ask questions across contracts, policies, PDFs, and email archives — and get cited, accurate answers instantly.
Our difference
We identify a specific, measurable problem first. We define success metrics and validate the approach — before a single line of code is written.
No preferred vendor, no referral arrangement. We recommend the right model for your use case — including open-source where it makes more sense than a paid API.
Where data sensitivity requires it, we deploy fully within your AWS, Azure, or GCP environment. Your data never leaves your infrastructure.
We can deliver the data warehouse, the analytics layer, and the AI on top — or just the AI layer if your data is already in good shape.
Discovery call
00:00Call notes
Not sure where to start with AI?
Tell us your problem — we'll tell you if AI is the right answer.
Book a Discovery Call30 minutes. No commitment.
We work best with businesses that have a specific, high-volume problem AI can genuinely solve — not those chasing the technology for its own sake.
FAQ
We are model agnostic. We work with OpenAI/GPT, Anthropic/Claude, and open-source models including Llama and Mistral via AWS Bedrock or self-hosted deployments. We recommend the right model based on your use case, data sensitivity, and cost requirements.
That depends on the model choice — and it's something we discuss explicitly during scoping. Where data sensitivity is a concern, we deploy open-source models in your own cloud environment so your data never leaves your infrastructure. Where third-party APIs are appropriate, we ensure your data handling meets your requirements.
RAG (Retrieval-Augmented Generation) lets an AI model answer questions using your own documents and data — not just its training data. It's the technology behind internal chatbots, document search, and knowledge base Q&A. If your team spends time manually searching for information or answering the same questions repeatedly, a RAG system is likely a good fit.
Off-the-shelf AI tools are built for the average use case. We build to your specific data, your workflows, and your business logic — deployed on your infrastructure with no per-seat or usage fees to a third party. You own everything we build.
For AI that relies on your business data — predictive models, analytics AI, forecasting — yes, clean structured data is essential. We offer end-to-end delivery: data warehouse, analytics layer, then AI on top. If your data is already in good shape, we can build the AI layer directly.
We start by identifying a specific, measurable problem — not a technology to explore. We scope the smallest solution that solves it, validate the approach before committing to a full build, and define success metrics upfront. We have no interest in AI projects that look impressive but don't move your business forward.