How we build the software your business runs on.
One team, end-to-end. Architecture, build, and ongoing operations. No handoffs, no pilots that never ship, no hourly retainers.
Four stages, no surprises.
Every engagement runs the same arc. The intro call is free. Everything else ships working software.
Intro call
A free 30-minute conversation. No slides, no demo, no script. We learn what your business actually does, the software running it today, and where the friction lives. If we're a fit, we send a fixed-fee proposal within a week. If we're not, we say so and point you somewhere better.
Scope
A paid engagement. We audit your current systems against what an AI-native system would consolidate, design the architecture, and ship the first working module so you see the system on real data, not slides. You finish Scope with software in production plus a written plan for the rest. Walk away after Scope and you keep what shipped.
Get started in as little as 2 weeks.
Build
Multi-stage development. Each stage adds a function and ships working software at the end. Stop after any stage and you keep what’s there. Most engagements take 3–6 stages; that’s a conversation, not a roadmap.
Operate
A monthly partnership. We run the system in production, and we run it like operators, not like a help desk.
- Keep the agents current. Models get deprecated, APIs change, the tools your agents depend on get updated. We migrate to new models, retune prompts when behavior regresses, and re-test against your real cases before anything ships.
- Catch drift before users do. Evals run on every change. Output quality, latency, cost, and error rates are monitored — when an agent starts to slip, we know before your team does.
- Retrain on your data. Edge cases, exceptions, and corrections feed back into prompts, retrieval, and policies. The system gets sharper on your business every month.
- Add what's next. New modules, new agents, new workflows as the business evolves — same foundation, same team.
Most clients stay on Operate indefinitely because the AI layer needs active care; some graduate to lower-touch.
Six systems we keep building.
Each one custom-built around a specific business and how it actually works.
Dispatch and operations platforms
Routing, scheduling, exception handling, and live operational visibility. AI agents handle the calls a dispatcher would: re-routing on traffic, escalating anomalies, summarizing the day at shift change. The team focuses on the edge cases, not the rote work.
Client portals with AI intake and routing
Customers upload, your team gets a summary. Documents auto-classify, the next step is suggested, nothing rots in an inbox. Built white-labeled, so clients see your brand and your team sees the system that runs underneath.
Internal ops dashboards with predictive signals
Real-time business metrics with anomalies surfaced before a human would notice. Reports that write themselves. Drill-downs that show why a number moved, not just that it did.
Custom CRMs and pipelines
Built for the way you actually sell. AI summarizes calls, classifies leads, drafts follow-ups, and updates records without anyone re-typing. Replaces the parts of Salesforce or HubSpot that don’t fit your motion.
Inventory, supply chain, and fulfillment tools
Demand forecasting, reorder points, and exception routing. AI watches the patterns; your team handles the edge cases. Built on top of whatever ERP or order system you already run.
Recommendation and merchandising engines
Learning systems trained on your catalog and customer behavior. Improves month over month on data your competitors don’t have. Wired into your storefront, your email, and your ad platforms.
Four patterns we build to.
Every system we build demonstrates at least one. Each one shows up in a live demo on real data.
Agents do the routine work.
The system runs jobs, not just helps people run them. The dispatcher reroutes drivers when traffic shifts. The intake agent processes new client paperwork end-to-end. The reconciliation agent matches invoices and escalates only what's off. You set the policy; the agents do the work and ask for help when they're unsure.
You talk to the system, you don't navigate it.
Natural language is the interface — to the data, to the agents, to the workflow. Ask "show me which clients haven't paid this month and have the follow-up agent draft replies in my voice" and the drafts arrive attached, ready to send. Not a chat widget glued to the side of a dashboard; the conversation is how work moves.
Decisions are baked into the workflow.
Classification, routing, prediction, anomaly detection. Not as separate "AI features" but as how work moves through the system. An invoice arrives → auto-classified, routed to the right approver, flagged if it's off-pattern. The decision is the workflow.
The agents stay current and learn your business.
We keep them sharp on two fronts. Outside in: models get deprecated, APIs change, the tools your agents depend on get updated — we run evals, upgrade models, and migrate agents so what worked last quarter still works this one. Inside out: trained on your decisions, your edge cases, your way of working — month one handles the basics, month twelve knows your business better than a new hire would.
Ready to talk about your system?
A 30-minute call. We'll figure out what software your business should be running on, and tell you whether we're the right team to build it.