AI that ships inside your product. Not a demo.

LLM-powered features, retrieval over your own data, and agentic workflows that automate real operations, built into the web and mobile products we already run, on your infrastructure, behind your login. The team adding the intelligence owns the architecture, so it lives in production, not a folder.

Assistant · in your app
Which accounts are at risk of churning this month?
Seven accounts show declining usage. Northwind and Acme dropped 40%+ this week.
Grounded in your data · no PII in the prompt
What this covers

Intelligence, wired into what you already run.

Not a standalone AI project bolted on the side. Features that live inside your product, grounded in your data, and owned by the team that built the platform.

LLM-powered features

In-product assistants, drafting, summarization, and classification: the language features users now expect, done well.

Retrieval over your data

RAG that answers from your own documents, tickets, and records, grounded, cited, and current, not hallucinated.

Agentic workflows

Multi-step automations that take real actions across your systems, with a human in the loop where it matters.

Document intelligence

Extraction and understanding over PDFs, forms, and contracts, turning unstructured paperwork into structured data.

Semantic search

Search that understands meaning, not just keywords, across your catalogue, knowledge base, or content library.

Evaluation & guardrails

The unglamorous half: test sets, safety rails, and monitoring, so the feature stays accurate and on-budget in production.

Why ours makes it to production

Most AI demos die in a folder. Ours ship.

The gap between an impressive prototype and a feature users trust is engineering: evaluation, guardrails, cost control, and integration. That gap is exactly what a senior product team is for.

Built into the product

The AI lives inside the app we already run — same data, same auth, same team — not a disconnected side project.

Grounded, not guessing

Answers are retrieved from your real data and cited, so users can trust, and verify what the model says.

Measured and monitored

We evaluate quality against real cases and watch it in production, so accuracy and cost don't drift silently.

You own the whole thing

The prompts, the pipeline, the data, and the IP are yours. Swap the model anytime. No lock-in to us or a vendor.

Trust & data

Your data governs what the AI can touch, in the contract, not the sales call.

A policy per client

What AI may touch is decided up front. If you forbid external models, that's a hard delivery constraint we enforce.

No PII in prompts

We build and test against synthetic data; agents get scoped, short-lived access, never your production secrets.

Auditable by design

Every AI action is logged and reviewable, so you can see what ran, on what data, and why.

The stack

Model-agnostic, by design.

We pick the model to fit the job and your data policy, and keep the door open to swap it as the field moves.

Models
OpenAIAnthropic ClaudeOpen-weight / self-hosted
Retrieval
Vector searchEmbeddingsRAG pipelines
Orchestration
PythonAgent frameworksEvalsObservability
It needs a product around it

AI is a feature of a product. Not a product alone.

Bring us the AI idea you’re unsure about.

In 30 minutes a founder will tell you whether it’s real, what it takes to ship it safely, and how it fits the product you already run, no hype, no vaporware.

Free · 30 minutes · with a founder · no deck, no pressure