Operational software for work that outgrew spreadsheets
The process works. The way it runs doesn’t.
We find the workflow held together by inboxes, spreadsheets, and tribal knowledge—then build the system that runs it.
Where we begin
Not with an “AI strategy,” but with the work that keeps getting stuck.
Most teams already know where the friction is. Information moves between PDFs, spreadsheets, inboxes, and business systems—and people hold the whole thing together.
What we build
One system. Every necessary layer.
Full-stack implementation—not a prototype handoff or a collection of disconnected automations.
Internal applications
Software shaped around the decisions, handoffs, and exceptions that make your operation distinct.
Interfaces · Workflow engines · ReportingAI-enabled workflows
Models handle extraction, classification, and assistance. Deterministic logic stays in charge of reliability—and of cost.
Documents · Analysis · Human reviewSystem integration
ERPs, databases, APIs, and cloud infrastructure connected into one observable production workflow.
NetSuite · AWS · Azure · APIsSelected systems
Built around work that has to function in the real world.
Duty recovery pulled out of 50-page carrier packets.
A nightly sweep that queues new vendor-bill attachments, triages every page, clusters pages into individual customs entries, extracts the filing and commercial-invoice fields under a strict schema, and pushes a one-click supporting excerpt back into the ERP for each entry.
A 37-step controlled procedure, executed on one screen.
One screen: scan the paperwork in an embedded capture pane, confirm the pre-filled fields, enter the serial, press confirm. Ten server-side operations then run as a durable background job, ending with the printed work-order tag.
Reading the quote bundle nobody has time to read.
A multi-pass pipeline that reads the whole bundle and produces that cross-reference automatically, seeding every discrepancy into a risk register and exporting the review workbooks. Pricing stays human by design.
The cloud tier for work an ERP cannot hold open.
A durable job platform beside the ERP: idempotent orchestration keyed by job ID, a queue with stale-job reclaim and deduplication, per-job cost telemetry, and a documented path to add a new job type without touching the business system.
A field-operations platform refined under years of real use.
A role-aware operations workspace joining inspection reporting, unit readiness, vendor coordination, maintenance dispatch, async processing, notifications, and dashboards.
A personal-finance product built from bank feed to decision support.
A React Native product backed by an event-driven AWS platform for bank sync, transaction logic, household finance, planning, alerts, and human-reviewed AI analysis.
How we work
From process knowledge to operating software.
The goal is not to automate everything. It is to build the right system around the work, with control where control matters.
Understand
Map the real workflow, its users, bottlenecks, data, and economics.
Design
Decide what belongs in software, automation, deterministic rules, and AI.
Build
Develop the interface, backend, integrations, infrastructure, and review loops.
Deploy
Put the system into production, observe it, and improve it with evidence.
The economics
Every model call is a bill that repeats.
Reducing AI agent costs is mostly a design problem: deciding where a model is genuinely required, and where ordinary code does the same job repeatably for nothing.
- 01No model · $0
Deterministic parsing
Input a rule can read is read by a rule. Most structured data never needs a model at all.
- 02Paid once · $0 after
Cached structure
The shape of a recurring document is learned once and reused by fingerprint on every later file.
- 03Cents per document
Model-proposed spec
The model describes how to read the file. Trusted code does the actual reading, and validates it.
- 04Metered per call
Direct extraction
The model reads the values itself, under a strict schema, when structure alone cannot resolve them.
- 05Most expensive · last resort
Vision on the page
Zoomed crops, checked character by character, for the handful of fields that must be exactly right.
Work escalates only when the cheaper rung fails, so the expensive path runs on the exceptions rather than the volume. In practice that is a cloud estate costing tens of dollars a month at rest, document bundles that cost a few dollars each to analyze, and re-runs that cost nothing because identical content is recognized instead of read again.
Engagement
Start with clarity. Build with purpose.
Cloud infrastructure · Business systems · Web and mobile products · Data and document pipelines · AI-assisted workflows · Integrations and automation
Process assessment
Current state, opportunity map, architecture, scope, and expected leverage.
Production build
Milestone-based implementation across product, integration, and infrastructure.
Continuous improvement
Optional support, monitoring, iteration, and expansion after launch.
Questions, answered
Before we begin.
What kinds of projects are a good fit?
Operational processes with real users, recurring volume, existing systems or data, and a clear cost to doing the work manually.
Do you only build AI products?
No. We build complete software systems. AI is one implementation tool, used only where it improves the workflow without weakening control.
Can you work with our ERP and existing tools?
Yes. Integrations with ERPs, databases, APIs, cloud services, and internal systems are central to the work.
How do you keep AI costs from growing with every user?
By treating a model call as a bill that repeats. Most document and data work has a deterministic path that runs correctly for nothing, so the model is reserved for the cases those paths genuinely cannot resolve. Results are content-addressed, which means seeing the same input a second time costs nothing.
Do we actually need an AI agent for this?
Often not, and we will tell you so. An agent earns its place where the next step truly depends on judgment. Where the work is a fixed sequence, a plain workflow is cheaper, faster, easier to test, and does not get more expensive as volume grows.
How does an engagement begin?
Usually with a focused process assessment: current state, opportunity map, proposed architecture, implementation scope, and expected leverage.
Your process is the starting point
What work should your team stop doing by hand?
Tell us how it works today. We’ll help turn it into a clear project brief.
Start the conversation