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AI & Machine Learning

Practical AI that pays for itself — not demos that die in a deck.

4–10 weeks to productionfrom $35/moSenior builder
Why it matters

Every business is being told to 'add AI'. Few are told where it actually creates margin. We start there: mapping your workflows to find the handful of places where a model genuinely removes hours or unlocks revenue — then we build exactly that.

Our builds run on production-grade foundations: Claude and GPT-class models behind typed APIs, retrieval pipelines over your own documents and data, evaluation suites so quality is measured rather than vibed, and guardrails so the system fails safely.

From AI customer support that resolves 70% of tickets, to document processing that eliminates data entry, to copilots inside your internal tools — we ship AI that your team trusts and your CFO can see in the numbers.

Capabilities

What we deliver

Six ways this shows up in real engagements — each scoped to your business, never lifted from a template.

LLM product features

Chat, summarization, generation, and copilot features inside your product.

Retrieval (RAG) systems

Answers grounded in your documents, policies, and data — with citations.

Document & data extraction

Invoices, contracts, and forms parsed into structured data automatically.

Support & sales automation

AI agents that resolve tickets and qualify leads, escalating gracefully.

Forecasting & analytics

Demand, churn, and revenue models built on your operational data.

Evaluation & guardrails

Test suites, monitoring, and safety rails so quality never regresses silently.

Outcomes

What you can expect

Not vibes — commitments. These are the results we design the engagement around, in writing, before we start.

A scoped AI roadmap ranked by ROI, not hype

Measured quality: eval suites run on every model or prompt change

Cost ceilings and caching so the token bill never surprises you

Human-in-the-loop escalation for every automated decision that matters

Tooling

The stack behind AI / ML

Proven, hireable, boring-on-purpose technology — chosen for the decade after launch, not the demo.

Claude API
OpenAI
Python
LangGraph
pgvector
Pinecone
Example builds

Example builds for AI / ML

Illustrative examples where this service does the heavy lifting — representative scenarios, not a client list, with the outcomes a build like this targets.

FAQ

Questions, answered

Straight answers to what founders and operators ask most before this kind of engagement begins.

Data never leaves your cloud without an explicit agreement. We use zero-retention API tiers, redact PII before inference where required, and can deploy fully inside your VPC for regulated workloads.

Three layers: retrieval grounding so answers cite your actual documents, evaluation suites that score accuracy on every change, and confidence thresholds that route uncertain cases to a human.

Most failed chatbots were prompts pointed at a website. We build systems: grounded retrieval, real integrations that let the AI actually do things, and measurement. The difference shows up in resolution rates within weeks.

Something we didn't cover? Ask us directly — a senior engineer answers, not a sales script.

Ready to build AI / ML?

The build costs nothing — services run from $35/mo once delivered. Book a free strategy call — you'll get an honest read on fit and your product plan in writing, whether or not you hire us.

Free strategy call · $0 until your product is finished · From $35/month