AI & LLM Solutions
Put modern AI to work — on your data, in your product.
Not a chatbot bolted onto your homepage. Real AI systems: fine-tuned models, retrieval over your documents, and agents that automate actual work — built by an engineer who has trained models and shipped multi-agent systems.
What we build
AI Integration
Add LLM features to your product or internal tools — assistants, summarization, extraction, classification, and semantic search — wired into your real data and workflows.
Custom & Fine-Tuned Models
When an off-the-shelf API isn't enough: task-specific models built end to end — data prep, fine-tuning, evaluation, and deployment.
AI Agents & Automation
Multi-step agent workflows that automate real processes, with guardrails, evaluation, and human-in-the-loop where it matters.
RAG / Knowledge Systems
Turn your documents and data into a reliable, cited question-answering system your team can trust.
AI Feasibility & Strategy
A short, honest engagement: what AI can and can't do for your specific problem — and what it would actually cost to build.
AI-in-the-loop Data Work
Use AI to clean, label, enrich, and route data at scale — the boring-but-valuable automation most teams never get to.
Why us
We don't lead with hype. We've built the unglamorous parts — evaluation harnesses, guardrails, data pipelines to feed the model — that separate a demo from something you can put in front of customers.
We'll tell you when AI isn't the answer
Half of good AI consulting is talking a client out of a model they don't need and into the automation they do.
FAQ
Do you build on top of OpenAI/Anthropic, or your own models?
Both. We start with the simplest thing that works — usually a hosted API — and only fine-tune or self-host when the data, cost, or privacy actually requires it.
Is my data safe and private?
We design for it: your data stays in systems you control where required, and we're explicit about what goes where.
We tried an AI pilot and it stalled. Why?
Usually no evaluation, no guardrails, and no data pipeline — a demo, not a system. That gap is exactly what we build.
How do you price AI work?
Feasibility calls are fixed-fee; builds are quoted after a short scoping phase.