Custom AI-native software
We build the AI-native software your business actually runs on.
Built around how your business actually works, operated by the same team that built it, so your people can get back to the work that matters.
- RoutedAnomaly · /pricing traffic·Down 23% vs. 7-day baseline
Alert sent to growth channel
- Auto-handledPickup window · Job 4435·Missed by 12 min · cause: prior stop
Customer notified · ETA updated
- RoutedLead · enterprise tier·Routed by ICP score · 87/100
Assigned to AE Marcus
- Needs reviewInvoice #4827·Vendor mismatch · price off 8%
Held for AP review
- Auto-handledShipment SH-9912·Delayed at customs · day 3
Buyer notified · alt shipper queried
Illustrative · agents handle the routine, escalate the rest.
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.
Client portals with AI intake and routing
Customers upload, your team gets a summary. Documents auto-classify, the next step is suggested, and nothing rots in an inbox.
Internal ops dashboards with predictive signals
Real-time business metrics with anomalies surfaced before a human would notice. Reports that write themselves.
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.
Inventory, supply chain, and fulfillment tools
Demand forecasting, reorder points, and exception routing. AI watches the patterns; your team handles the edge cases.
Recommendation and merchandising engines
Learning systems trained on your catalog and customer behavior. Improves month over month on data your competitors don’t have.
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.
Four stages, no surprises.
Every engagement runs the same arc. The intro call is free. Everything else ships working software you can see.
Intro call
A free 30-minute conversation. No slides, no demo. We learn what your business actually does and what software is failing it today.
Scope
A paid engagement. We audit your current systems, design the architecture for your AI-native software, and ship the first working module so you see the system on real data, not slides.
Get started in as little as 2 weeks.
Build
Multi-stage development. Working software at the end of every stage. Stop after any stage and you keep what shipped.
Operate
A monthly partnership. We run the system in production like operators: keep the agents current as models, APIs, and tools change, catch drift before users do, retrain on your edge cases, and add new modules as the business evolves.
The other ways businesses spend their AI budget.
Most AI spending lands in one of five traps. Cloudfinch is the sixth option.
Them
Cloudfinch
Where we do our best work.
We turn down projects that aren't a fit. Here's how we read one.
We're a fit if you're
Not a fit if you want
Numbers from shipped work.
Before/afters from systems we've built since 2012.
Building custom software since
From kickoff to first working module in production
End-to-end, no handoffs
Per engagement, no hourly retainers
“Cloudfinch delivered our logistics platform’s MVP in just four weeks. We went from manual Excel tracking to automated route optimization — saving 15 hours a week.”
“The custom scheduling system Cloudfinch built replaced three separate tools and cut our operational workload by 40%.”
Common questions, straight answers.
Everything you need to know about working with us. Still have questions? Book a call.
With a 30-minute call. No slides, no demo. A working conversation about your business, the software running it today, and where AI-native software would actually pay off. If we’re a fit, we send a fixed-fee proposal within a week.
No. It’s a diagnostic. We’re trying to figure out whether there’s a real system worth building and whether we’re the right team to build it. If the problem isn’t ready yet, we say so. If it’s outside what we do well, we say that too.
Sometimes. Often partially. We integrate where the SaaS is the right tool and replace where it isn’t. Most engagements replace some categories of SaaS and integrate with others. The intro call figures out which.
Most engagements start with the single most painful piece. You don’t have to commit to replacing your stack. Run one piece on software built for you, see how it goes, and we figure out what’s next from there.
You own the code. We document the system as we build it. Operate is a service, not a dependency. Most clients stay because the AI layer needs active care, not because they can’t leave.
Your business data stays in systems you control. We use API-tier models from OpenAI, Anthropic, and Azure OpenAI that do not train on customer inputs, and for sensitive workloads we run smaller open models inside your cloud (AWS, GCP, or Azure tenant). The exact data-handling boundary is agreed in writing before any data leaves your environment, and we sign NDAs and DPAs as standard.
We engineer for a predictable monthly run cost: caching repeated calls, sizing prompts carefully, and routing the easy 80% of traffic to cheaper models. You see a projected monthly bill in the proposal. If a provider deprecates a model or changes pricing, swapping it out is part of what Operate covers. You’re not locked into one vendor’s roadmap.
Latest from our blog
Notes, essays, and short reads on building AI-native software for operating businesses.
Tell us what you're building.
A 30-minute call. We'll figure out whether AI-native software is the right move for your business. If it isn't, we'll tell you and save you the cycles.