Services

AI-Driven Development

AI integrated where it actually moves a metric. We design, ship, and run intelligent features inside your existing software — without rewriting your product.

Where AI actually earns its keep

Use cases we ship most often.

Conversational interfaces

Chatbots and copilots over your data — internal tools, customer support, sales assist. RAG-backed with citations and guardrails.

Search & retrieval

Semantic and hybrid search over documents, tickets, code, and structured data. Embedding pipelines + reranking.

Structured extraction

Pull structured data out of PDFs, emails, contracts, and unstructured text — with schema validation and confidence scoring.

Agents & workflows

Multi-step LLM workflows that take action — tickets, approvals, routing, escalation — with audit trails and human-in-the-loop.

Smart suggestions

In-product AI suggestions, drafts, summaries, and recommendations that integrate cleanly with your UX.

Eval & observability

Offline evals, regression tests for prompts, cost dashboards, and quality metrics — so AI behaves predictably in production.

How we approach AI

Practical, transparent, and built to survive a model upgrade.

Model-agnostic by default

We work across Claude, GPT, Gemini, and open-source models. We pick by the workload, not the vendor demo.

Retrieval first, fine-tuning last

Most "AI" problems are retrieval problems. We get the data right before reaching for fine-tuning or larger models.

Evals before scale

If you can't measure it, you can't ship it. We build eval suites alongside the features themselves.

Guardrails, not vibes

Schema-validated outputs, PII redaction, prompt injection mitigations, and clear escalation paths to humans.

Cost & latency are features

Caching, batch routing, smaller models where they're enough, and visibility into per-feature cost.

Data stays where it should

Cloud, on-prem, or hybrid. We respect your data residency and compliance constraints.

Starting points

AI readiness review

Two-week assessment: where AI fits in your product, what data is ready, what to build first, and what to skip.

Prototype sprint

Four-week sprint to a working prototype on real data with an honest eval — go/no-go decision at the end.

Production AI feature

Full implementation: ingestion, retrieval, prompts, evals, observability, and the UI inside your existing product.

Thinking about adding AI?

Tell us the problem you're trying to solve. We'll tell you honestly whether AI is the right tool and what the cheapest path to value looks like.

Book an AI consultation