AI features that survive production, not demos that die in a notebook.
Most AI projects stall between the prototype and production. We build the unglamorous parts that make AI dependable: evaluation suites, retrieval pipelines, guardrails, observability, and cost budgets, so the feature your users see keeps working after launch.
What we deliver
AI & Machine Learning, delivered as working software
LLM product features
Copilots, assistants, document intelligence, and workflow automation built on Claude, GPT, or open-weight models, with structured outputs and fallbacks.
RAG & search pipelines
Retrieval systems over your documents and data: chunking strategy, embeddings, hybrid search, reranking, and citation-grade answers.
Evaluation & guardrails
Automated eval suites, red-team test sets, prompt regression testing, and content guardrails so quality is measured, not assumed.
ML & data systems
Forecasting, classification, and recommendation models with the data pipelines and monitoring they need to stay accurate.
How we work on ai & machine learning projects
- Evaluation-first: every AI behavior has a test suite before it ships
- Token and latency budgets tracked from the first sprint
- Model-agnostic architecture that lets you swap providers without a rewrite
- Human-in-the-loop and fallback paths for the failure cases
Technologies we reach for
Chosen for reliability and hireability, so your future team will thank you.
- Claude API
- OpenAI API
- LangGraph
- pgvector
- Pinecone
- Python
- TypeScript
- Vercel AI SDK
Engagement
Four steps from first call to production
- 01
Scope call
A shared problem statement and honest feasibility read.
- 02
Fixed proposal
A fixed-scope proposal you can take to your board.
- 03
Weekly sprints & demos
Deployed increments every week, visible in staging.
- 04
Launch & support
A shipped product, a support line, and zero lock-in.
Proof
AI & Machine Learning work we can show you
SaaS · B2B software company
Deflecting 62% of support tickets with a grounded AI assistant
A retrieval-grounded AI support assistant that resolves 62% of inbound tickets with answers cited from the client's own documentation.
Read case studyFintech · Consumer lending fintech
Cutting loan decisions from 4 days to 7 minutes
A digital lending platform with automated underwriting that took loan decisions from a 4-day manual review to a 7-minute automated flow.
Read case studyFAQ
AI & Machine Learning: common questions
Specific answers for this service. For pricing, ownership, and process questions, see the FAQ on our homepage.
Ready to scope your ai & machine learning project?
Book a free consultation and we'll map your requirements to a fixed-scope plan with real numbers, in one call.
We reply within 1 business day.