Four services.
Plain-language descriptions
of what you actually get.
No pricing on this page — every project is scoped to what's actually needed. Pricing comes after a 30-minute call.
Apps that don't fall over the day after launch.
We build web apps end to end — database, API, front-end, auth, billing, the deploy pipeline that puts it live. Usually TypeScript, React, Postgres, and whichever cloud you already pay for.
Problems it solves
- —MVPs glued together in no-code that have stopped scaling
- —Internal tools running on a spreadsheet and one tired person
- —Three-month freelancer engagements that left undocumented code behind
Who it's for
Founders shipping their first real product, ops teams replacing a spreadsheet, and product teams who need a second pair of hands for two quarters.
Real example
Booking platform for a regional services company
Replaced a 14-tab spreadsheet with a customer-facing booking flow, an internal dispatch board, and Stripe billing. Ten weeks from kickoff to first paying customer. We still ship updates on a monthly cadence.
What the process looks like
- 01Week 1 — scope, wireframes, technical decisions written down
- 02Weeks 2–8 — weekly demo, working software in staging from day one
- 03Week 9 — go-live, monitoring, runbooks
- 04After — optional monthly retainer or full handover to your team
What you walk away with
- ✓Production app on your accounts, your domain, your repo
- ✓A test suite a new developer can actually run
- ✓Docs that explain *why*, not just *how*
LLMs wired into the work you already do.
We add language models to existing products and workflows — summarising tickets, drafting replies, extracting structured data from messy documents, semantic search across your knowledge base.
Problems it solves
- —Teams pasting things into ChatGPT and copying answers back, one ticket at a time
- —Existing AI features that hallucinate too much to ship
- —Decision paralysis between OpenAI, Anthropic, open-source models, and the marketing around all three
Who it's for
Companies with a working product and a clear repetitive task that takes a human longer than it should. Not a fit if you're looking for 'an AI strategy' — we're builders, not consultants.
Real example
Document intake for a legal-adjacent company
Built a pipeline that takes scanned PDFs, extracts structured data with a constrained LLM, flags edge cases for human review, and pushes the rest to their CRM. Cut intake time from twenty minutes per file to forty seconds.
What the process looks like
- 01Eval first — we measure the current task before we touch a model
- 02Prototype against your real data, not a demo dataset
- 03Ship with guardrails, structured outputs, and a fallback path
- 04Monitor accuracy in production and tune from there
What you walk away with
- ✓An AI feature you can defend in a board meeting
- ✓Cost-per-call you actually understand
- ✓Code that's portable across providers — no lock-in to one vendor
Quietly handle the work no one wants to do.
Multi-step automations that read email, talk to APIs, call models when judgment is needed, and write back to your systems. The boring jobs that take three apps and a human to complete.
Problems it solves
- —Manual handoffs between tools (inbox → CRM → spreadsheet → Slack)
- —Approval workflows that depend on one person being awake
- —Lead routing, invoice processing, support triage, content reformatting
Who it's for
Operations teams with one or two clearly defined repetitive workflows. We start narrow — one agent, one job, observable — before adding more.
Real example
Inbound lead triage for a B2B SaaS
Agent reads inbound demo requests, enriches the company from public data, scores fit against an ICP, routes hot leads to a salesperson with a draft reply, and files the rest with notes. Salesperson confirms or edits — never starts from scratch.
What the process looks like
- 01Map the current workflow with the people who actually do it
- 02Build the narrowest possible agent, run it in shadow mode
- 03Flip it on for one user, measure for two weeks, then expand
- 04You get full logs of every action so it's never a black box
What you walk away with
- ✓Hours back to your team each week
- ✓Audit trail of every decision the agent made
- ✓Clear off-ramp — agents can be turned off without breaking the workflow
Get found by people already searching for you.
Technical SEO, content strategy, and on-page work. No link schemes, no keyword stuffing, no 'AI-generated SEO content at scale' — that stuff stopped working a year ago and we're not interested in fighting Google's spam team for you.
Problems it solves
- —Sites that rank for the company name and nothing else
- —Blog posts that get traffic but no customers
- —Migrations that quietly tanked organic visibility
Who it's for
Companies with a real product and at least some genuine expertise to share. SEO works when there's something worth ranking for.
Real example
B2B fintech with deep technical content
Audited and rebuilt forty existing posts, restructured the site architecture, fixed crawl issues from a year-old migration, and shipped a publishing cadence the in-house team could maintain. Non-brand organic traffic tripled over nine months.
What the process looks like
- 01Technical audit — what's stopping the site from being indexed properly
- 02Content audit — what's worth keeping, fixing, or removing
- 03Strategy doc with topics, formats, and a realistic cadence
- 04Either we write it, or we coach your team to
What you walk away with
- ✓Higher rankings on the searches that actually convert
- ✓A site structure that won't fight you on the next launch
- ✓Reporting that ties traffic to revenue, not just impressions