What we take on.
A short list, on purpose. SaaS products, AI features, internal platforms, and the integrations that make them work in the rest of your stack. Each engagement is two or three senior engineers from start to ship.
SaaS product engineering
We build SaaS products that scale past the founding team. Multi-tenant from the first version, with auth, billing, and an admin already in place.
Most engagements start with the version that goes in front of paying users, then keep going as the product finds its shape. We're opinionated about what to build first and what to defer, and we'll tell you when an idea is going to cost more than it earns.
What's included
- Multi-tenant architecture
- Stripe billing and subscriptions
- Auth, RBAC, audit logs
- Admin and customer dashboards
- Usage metering and quotas
- Onboarding that users finish
AI applications
The model is rarely the hard part. We spend most of the time on the interface, the eval set, and what should happen when the model is wrong.
We build assistants, retrieval systems, and agentic workflows for products where being wrong has a cost. That means real evals, citations users can verify, and a refusal pathway tuned against questions you actually get.
What's included
- Retrieval (BM25, dense vectors, re-ranking)
- Agentic workflows with tool use
- Eval harness and regression runs in CI
- Streaming UIs and tool-call UX
- Citations and refusal pathways
- Cost and latency budgets
Internal platforms
Most internal tools start as a spreadsheet and never recover. We build the software ops, finance, and support teams actually want to open every day.
These projects pay for themselves quickly, usually by replacing two or three tools you were already paying for. We read from the systems that already hold the truth, so there's no migration to argue about before anyone sees value.
What's included
- Custom CRMs and admin consoles
- Workflow and approval systems
- Reporting and BI surfaces
- Role-based access and audit trails
- Integrations with existing stack
- Migration from legacy systems
Automation systems
Scheduled pipelines that move data, files, and decisions. The retries actually work, and the dashboards make sense at 2am.
We treat automation as production software. Dead-letter queues, replay tools, idempotent ingestion, and the kind of observability that lets you debug the run from two weeks ago without git-bisecting your way to it.
What's included
- Event-driven workflows
- Data pipelines (ETL/ELT)
- Document and form processing
- Scheduled jobs at scale
- Observability and alerting
- Human-in-the-loop review
Full-stack engineering
One team across the stack: design, frontend, backend, infrastructure. The same person who picks the database picks the empty state.
Fewer handoffs means fewer 'that was someone else's job' bugs, and the system degrades more gracefully when something breaks. We pick the boring database, the boring queue, and the boring deploy pipeline whenever we can.
What's included
- TypeScript across the stack
- Postgres, Redis, queues
- Serverless and containerized runtimes
- CI/CD, IaC, observability
- Performance budgets and SLOs
- Security review and threat modeling
API integrations
Integrations are boring until two systems disagree about what happened. We design for that day from the start.
Most of the work is being correct under conditions no demo ever covers: webhooks that fire twice, rate limits at the wrong moment, partial outages, schema drift. We build with replay, reconciliation, and idempotency from the first commit.
What's included
- Stripe, HubSpot, Salesforce, Segment
- Webhook ingestion at scale
- Idempotency and reconciliation
- Backfills and replay
- Internal SDKs and typed clients
- OpenAPI specs
UX and interface engineering
Type, density, motion, and accessibility are engineering decisions. They get made in the code, not negotiated through screenshots after the fact.
Design and engineering live in the same repo. Components get drawn against real data, in the actual stack, on the actual screens. No Figma frames waiting for a translation pass.
What's included
- Design systems in code
- Component libraries (shadcn, Radix)
- Type, motion, accessibility
- Dashboard and data UI
- Marketing sites and product surfaces
- Cross-platform consistency
Two or three engineers,
six to fourteen weeks.
You get a senior team that doesn't change mid-project. We'll know your codebase, your customers, and what you're trying to avoid by the second week.