STUDIO · PRODUCT DEVELOPMENT

We ship your AI products.

A senior pod — product, design, ML, eval, platform — embedded with your team. Web, mobile, desktop, voice, and agents. 90 days to production. Working software every sprint. No pyramid billing.

THE POD

Six roles. One accountable pod.

A pod is the unit of delivery. Senior, cross-functional, and paired with two of your engineers from day one so ownership actually transfers.

Product Lead

Owns roadmap, exec relationship, trade-offs. Veteran PM with AI scars.

01
Product Designer

Designs how people interact with AI. Trust, transparency, sources, and the option to undo — by default.

02
ML Engineer

Builds the models, retrieval, and agents. Picks the simplest thing that works — then makes it robust.

03
Eval Engineer

Builds the test sets and quality checks that keep the product accurate after launch — not just on demo day.

04
Platform Engineer

Deployment, single sign-on, monitoring, and cost control. Hands your infra team a runbook they can own.

05
Delivery PM

Cadence, ceremonies, stakeholders. Keeps a fast-feedback pod actually fast.

06
WHAT WE BUILD

Eighteen kinds of AI product. One senior pod.

Every pod ships in one of these shapes — from a narrow copilot to a full platform. We pick the smallest thing that answers the business question.

Web copilot

In-app assistant with context, actions, and audit trails. The starter build for most enterprises.

8–12 weeksMost popular

iOS & Android apps

Swift / Kotlin native with on-device inference, voice-first flows, multi-modal capture.

12–16 weeksNative

Agent platform

Tool-calling agents, human-in-the-loop, audit log, policy engine. For complex internal workflows.

12–14 weeksComplex

Conversational search

RAG over your docs and data. Source-cited, eval-gated, faster than your CMS search.

6–8 weeksRAG

Voice AI

Real-time voice surfaces — wake words, interruption, TTS tuned to your brand.

10–12 weeksVoice

Analytics copilot

Natural-language data surfaces on top of your warehouse. Governed SQL, guardrailed charts.

8–10 weeksData

Forecasting systems

Demand, risk, revenue. Classical ML in the core, LLM for explanation and UX.

10–14 weeksML

Generative UX surface

UI that rebuilds itself around the task — schema-driven, eval-guarded. For novel UX bets.

10–12 weeksNovel

Document intelligence

Structured extraction from PDFs, contracts, clinical notes. Human-in-the-loop by default.

6–10 weeksOCR+LLM

Eval harness

Regression, drift, red-team. Your second line can sign off. Pays for itself by month three.

4–6 weeksGovernance

Pricing & promo AI

Elasticity-aware pricing, promo ROI, markdown optimization for retail and CPG.

10–12 weeksRevenue

Recommendation systems

Hybrid retrieval + LLM re-ranking for commerce, content, and internal knowledge products.

8–10 weeksPersonalization

Anomaly detection

Fraud, AML, SLA drift, supplier risk. Explanations that second-line teams can defend.

8–12 weeksRisk

AI workflow automation

Replaces RPA + macros with LLM-driven flows. Exception handling that actually handles exceptions.

8–10 weeksOps

Knowledge platforms

Internal answer engines built on RAG, permissions, and source-grade citations. Good change management.

10–12 weeksKnowledge

Vision & multi-modal

Image, video, and document vision surfaces. Medical, industrial, and retail deployments.

10–14 weeksVision

Fine-tuning program

When prompting isn't enough. Data curation, SFT, evaluation, deployment, and handover.

6–10 weeksCustom models

Real-time systems

Low-latency inference at the edge or in-session. For voice, trading, ops, and live UX.

10–14 weeksLatency
HOW WE SHIP

Five-step delivery rhythm. Working software every sprint.

01
Brief & scope

A single working-session — scope, metrics, risks, and what "done" means.

02
Architect & eval

Reference architecture and the eval plan that gates every release from day one.

03
Ship sprint-by-sprint

Two-week cadence. Working software at every review. No "trust us" slides.

04
Users by week six

Beta cohort live. Real signal replaces opinion. Eval harness already running.

05
Handover & run

Runbook, on-call rota, and your team paired and trained to run it without us.

OUR STACK

Opinionated, model-agnostic, boringly reliable.

We pick tools based on what's running in production, not hype — and port cleanly when the landscape changes.

Models
  • Anthropic Claude
  • OpenAI GPT & o-series
  • Google Gemini
  • Meta Llama / open-weights
  • Cohere, Mistral
  • AWS Bedrock & Azure AI
Frameworks
  • Next.js + React
  • Swift / Kotlin native
  • LangChain, LlamaIndex
  • Vercel AI SDK
  • FastAPI / Node services
  • tRPC & GraphQL
Data & infra
  • Postgres + pgvector
  • Pinecone, Weaviate
  • Snowflake, Databricks, BigQuery
  • Kafka & streaming
  • Temporal, Inngest
  • Kubernetes, Docker, Terraform
Eval & observability
  • LangSmith, Braintrust
  • Weights & Biases
  • Datadog, OpenTelemetry
  • Custom eval harnesses
  • Red-team & jailbreak suites
  • Cost & drift dashboards
ENGAGEMENT MODELS

Three ways to bring us in.

01 · Pilot

Single v1 build

90 days · one pod

You've chosen the first bet. We scope, architect, ship production v1, and hand it to your team.

  • Working software by week 4
  • Users by week 6
  • Production by week 12
  • Runbook & eval harness
Start here →
03 · Embed

Embedded team

Ongoing · senior specialists

We place one or two senior specialists inside your product org to pair, mentor, and unblock for a quarter or more.

  • Paired delivery with your engineers
  • Architecture & eval oversight
  • Hiring & onboarding support
  • Exit plan from day one
For mature teams →
CASE STUDIES

10+ shipped products, three operating outcomes you can verify.

Healthcare · Clinical

Triage copilot for a regional health system

EHR-integrated intake assistant for a network of 14 urgent-care clinics. Specialty-aware, evaluator-reviewed weekly, with a human-in-the-loop escalation path.

31%
Faster intake-to-first-read
12
Weeks to production
0
Escalated incidents post-launch
triage · live
→ patient.intake → ortho-urgent
→ specialty: orthopedic
→ priority: P2 · 14 min
→ EHR sync · attached
Finance · FP&A

Variance-narrative copilot for a global CPG

A reconciliation copilot that reads ERP variances and drafts the monthly commentary for the close team. Eight hours per close, back in the analyst's week.

8h
Reclaimed per close cycle
$1.4M
Annualized productivity
3
Markets, rolling out
m11 close · variance
→ NA · revenue +2.3%
→ EU · cogs −4.1% (driver: freight)
→ APAC · opex +0.7%
→ draft commentary · ready
Banking · RM productivity

Relationship-manager copilot for a top-20 bank

Pulls account context, drafts outreach, logs back to CRM. Deployed to 300 RMs, expanded to wealth & private banking within two quarters.

22%
More client conversations / month
300
RMs on the platform
2Q
To expansion
rm · client brief
→ Acme Industries · $84M AUM
→ next-best: term-loan refi
→ draft outreach · 2 variants
→ CRM sync · logged
NEXT STEP

Bring us the problem. We'll bring the pod.

Most engagements start with a 60-minute brief. By the end of it, you'll know whether we're the right team — and what shipping v1 would actually look like.