AI Automations
Replace manual workflows with AI that runs in production.
- Lead scoring
- Document processing
- Support classification
- Inbound triage
Senior engineers shipping in weeks. Milestone-gated phases. You own the code at handoff.
Case studies published once clients clear them for use.
We don't build websites or apps as a category — we build the operational outcome you need, in whichever format fits. These four cover most of what mid-market operators ask us for.
Replace manual workflows with AI that runs in production.
Wire AI into the tools you already use.
Ship the SaaS feature your team can't get to this quarter.
Replace the spreadsheets running your business.
Every engagement is milestone-gated — fixed scope per phase, working deliverable at the end of each, exit when you want. You're never six months into a vendor lock with a half-built thing.
We map your problem, scope the solution, write the architecture doc. You exit with a deliverable even if we don't move forward.
System design, stack choices, sequencing. The build plan you'll see ship — costs, milestones, dependencies, all of it.
Working software at the end of every milestone. Stop whenever — you keep what's shipped, not a half-built thing.
Production deploy, monitoring, full handoff. Code, docs, deployment — yours. No lock-in unless you ask for retainer.
No junior pass-through.
Every engineer on your project has shipped this kind of work before — AI in production, custom SaaS in market, internal tools at scale.
Fixed scope per phase.
Working deliverable at the end of each. Stop after any milestone and you keep what shipped — not a half-built thing with an open invoice.
Repo, docs, deployment — yours.
We don't lock you into a maintenance dependency. Retainer is opt-in, not the price of working with us.
Every AI automation we deliver is evaluated, monitored, and owned by you at handoff. The thing that wins a hackathon is not the thing that handles 50,000 production runs a month without paging your team at 3am.
Claude, GPT, Gemini. We pick by capability per workflow, not by hype.
Llama, Mistral, Qwen. For self-hosting, fine-tuning, cost control, or regulatory reasons.
Grounding in your data so the model answers from what you know — not what its training set guessed.
When the workflow has decisions to make and tools to call, not just text to generate.
Model-context-protocol integrations so AI calls into your stack the way a developer would.
Every prompt, every output, every regression caught before a customer sees it.
Every AI step logged, every failure traceable, every output reviewable. You audit the system.
Swap models without rewriting consumer code. Vendor risk priced down to a config change.
The integrations and tools we ship keep working regardless of which model wins next year. Every AI step is instrumented so you can swap providers without rewriting the system.
Our model is built for that exact anxiety. Discovery is fixed-scope and you exit with an architecture doc whether or not we continue. Build phases are milestone-gated — two-to-four weeks each, working software at every milestone, stop whenever. You're never six months into a vendor lock with a half-built thing.
Three things. Senior-only — every engineer on your project has shipped this kind of work before. Outcome-owned, not hourly — fixed scope per phase, not invoice-by-the-hour. And we ship the thing — production deploy, monitoring, handoff — we don't just write code and email you a zip. If those three don't matter for your project, staff-aug is cheaper and that's fine.
Two reasons people do it. One: unblock work your team can't get to this quarter — internal tools, AI integrations, the things the product roadmap never makes room for. Two: plug a gap while you hire — we hand off cleanly when your team has capacity. We don't compete with your engineers; we work next to them.
The integrations and tools we ship keep working regardless of which model wins. Every AI step is instrumented so you can swap providers without rewriting the system. The deliverable isn't "we used Claude" — it's "we built a classifier that processes your tickets, with eval coverage and observability, that you can route through any frontier or open-source model without changing the consumer code."
Discovery phase. Fixed scope, two weeks, fixed price. You see how we work — the questions we ask, the architecture we propose, the team we put on it. You exit with an architecture doc and a build plan that any team could execute against. If we're not the right fit you walk with a usable document and no further commitment.
When the workflow is simple, the volume is low, and the integration depth is shallow — no-code is genuinely the right choice and we'll tell you. We build the 20% no-code can't reach: AI-heavy workflows, high-volume processing, custom business logic, multi-tenant SaaS, deep integrations with private APIs. If your problem fits no-code, save the budget.
We'll tell you in the first 10 minutes whether we're the right fit — or whether you should hire in-house, use no-code, or pick a different agency.
Book a discovery call