Services

Engineering,
in depth.

Everything we build falls into four disciplines. Here's what each engagement looks like — the problems we solve, how we work, and what you walk away with.

Custom Software ProductsData Infrastructure & AnalyticsGenerative AI & LLM ProductsConsultation & R&D

01 — Product MVPs & full-stack builds

Custom Software Products

We design, build, and ship custom software products end to end — from a validated idea to a launched, scalable product. One senior team handles design, engineering, and deployment, so you get a real product in front of users in weeks, not quarters.

Problems we solve

A validated idea but no technical team to build it
An investor demo deadline and nothing to show yet
A prototype that can’t survive real users
Agencies that deliver slideware instead of software
Off-the-shelf tools that don’t fit how you actually work
Early technical decisions you’ll regret at scale

How an engagement runs

1

Scoping workshop

We cut your idea to the sharpest possible v1 — what ships now, what waits.

2

Design sprint

Flows, wireframes, and a UI system that looks like a funded company.

3

Weekly build increments

Working software every week, live at a URL you can share.

4

Launch

Production deployment with analytics and monitoring from the first user.

5

Iterate

Post-launch support and a roadmap driven by real usage data.

Technologies we use

Next.jsReactReact NativeTypeScriptNode.jsPythonPostgreSQLStripeVercelAWSGitHub Actions

Industries we support

Startups & VC-backedB2B SaaSMarketplacesConsumer appsInternal tools

What you walk away with

  • A deployed, production-grade product
  • Product design: user flows, UI system, and launch-quality polish
  • Full source code, documentation, and CI/CD
  • Analytics and error monitoring wired in
  • Launch support and an iteration roadmap

Expected outcomes

2–4 weeks
from kickoff to a working MVP
Investor-ready
a product you can demo with confidence
Built to grow
an architecture that scales past launch
Schedule a consultationRequest a proposal

02 — Pipelines, warehouses & analytics

Data Infrastructure & Analytics

We design and build the data backbone your business runs on — pipelines that move data reliably, and analytics platforms that turn it into decisions. From your first warehouse to streaming at scale, we engineer for correctness, cost, and speed.

Problems we solve

Data scattered across tools with no single source of truth
Reports built by hand, days out of date by the time they land
Legacy ETL that breaks silently and nobody trusts
Dashboards that disagree with each other
Cloud data costs growing faster than the business
Teams that want to be data-driven but can’t get to the data

How an engagement runs

1

Audit & discovery

We map your sources, systems, and the questions your teams need answered.

2

Architecture design

A pragmatic blueprint: warehouse, pipelines, modeling, and governance.

3

Incremental build

Pipelines land in production from week one — value early, not at the end.

4

Validation & QA

Data tests, reconciliation against source systems, and performance tuning.

5

Handover & enablement

Documentation, runbooks, and training so your team owns it confidently.

Technologies we use

PythonSQLApache AirflowdbtApache SparkKafkaSnowflakeBigQueryPostgreSQLTerraformAWS · GCP · Azure

Industries we support

E-commerce & retailFinTechHealthcareSaaSLogistics & supply chain

What you walk away with

  • Production data pipelines with orchestration and alerting
  • Cloud warehouse or lakehouse, modeled and documented
  • Analytics layer: dashboards and self-serve BI
  • Data quality test suites and monitoring
  • Architecture documentation and runbooks

Expected outcomes

One source of truth
every team working from the same numbers
Minutes, not days
from data landing to decision-ready
Lower cloud spend
pipelines tuned for cost from day one
Schedule a consultationRequest a proposal

03 — LLM apps, RAG & AI agents

Generative AI & LLM Products

We build generative AI products that do real work — assistants grounded in your data, agents that automate workflows, and RAG systems with answers you can audit. Everything ships with evaluation and guardrails, so it holds up in production.

Problems we solve

Institutional knowledge trapped in thousands of documents
Support teams drowning in repetitive questions
Manual document workflows that consume expert hours
AI prototypes that impressed in the demo and failed in production
Hallucination and compliance risk blocking AI adoption
No way to measure whether an AI feature actually works

How an engagement runs

1

Use-case discovery

We find the workflows where AI creates measurable value — and skip the gimmicks.

2

Data & retrieval design

Chunking, embeddings, and retrieval tuned to your documents and access rules.

3

Prototype & evaluate

A working system in weeks, scored against an evaluation set — not vibes.

4

Hardening

Guardrails, grounding, fallbacks, and monitoring for safe production behavior.

5

Deploy & improve

Live rollout with usage analytics and continuous quality tracking.

Technologies we use

Claude & GPT APIsRAG pipelinesLangGraphpgvectorPineconeEmbedding modelsEvaluation suitesAWS BedrockAzure OpenAI

Industries we support

Legal & professional servicesHealthcareFinancial servicesCustomer supportMedia & education

What you walk away with

  • A production generative AI product
  • Retrieval pipeline over your documents with access control
  • Evaluation suite with accuracy benchmarks
  • Guardrails, monitoring, and usage analytics
  • Integration into your existing tools and workflows

Expected outcomes

Cited answers
every response traceable to a source
Measured quality
accuracy tracked against evaluation sets
Hours back
expert time freed from repetitive work
Schedule a consultationRequest a proposal

04 — Advisory, prototyping & applied research

Consultation & R&D

Sometimes you don’t need a full build — you need senior engineers to think alongside you. We advise on architecture and technology strategy, prototype the risky parts, and run applied research so you can commit to a direction with evidence, not guesswork.

Problems we solve

A big technical decision with no in-house expert to pressure-test it
A promising idea that needs a prototype before you can fund it
An AI or data opportunity you can’t yet size or scope
An architecture you suspect won’t scale — but aren’t sure why
A team that needs a second opinion from people who’ve built it before
Research questions that never make it out of the backlog

How an engagement runs

1

Framing

We turn a fuzzy question into concrete hypotheses and success criteria.

2

Deep dive

Architecture review, technology assessment, or a tooling and literature scan.

3

Prototype

A focused proof of concept that tests the riskiest assumption first.

4

Findings

Clear recommendations, trade-offs, and a costed path forward.

5

Handover

Documentation and a roadmap your team can act on — with or without us.

Technologies we use

Architecture reviewProof of conceptTechnical due diligenceLLM evaluationBenchmarkingPythonJupyterCloud sandboxes

Industries we support

Startups & VC-backedScale-upsInvestors & due diligenceEnterprise innovationResearch-driven teams

What you walk away with

  • An architecture or technology assessment with clear recommendations
  • A working proof of concept for the riskiest part
  • Benchmarks, evaluations, or a research report
  • A costed, sequenced roadmap forward
  • Documentation your team can build on

Expected outcomes

Decide with evidence
commit to a direction backed by data
Risk retired early
the hard part proven before you invest
A clear path
a sequenced, costed plan to execute
Schedule a consultationRequest a proposalStart with a review

Not sure which service fits?

Most projects touch more than one discipline. Tell us where you are — we'll recommend the shortest path to something working.

Schedule a consultationRequest a proposal