Evidence in the system.
We use our own operating environment to confront the difficult parts of applied AI: fragmented data, real workflows, edge cases, permissions, integrations, and human accountability.
StonegateOS
A connected operating platform created around the requirements of a service business—from customer acquisition and quoting to field execution, partner coordination, intelligence, and oversight.
The public repository shows a production-oriented monorepo spanning a customer website, desktop Team Console, phone-first field application, Partner Portal, API services, and durable workers.
Explore the case studyAI-assisted work, connected to the record.
Recorded calls become structured documentation, next steps, and coaching signals.
“Ideally Thursday the 24th, sometime after 10. We have freight elevator access.”
Customer requested office cleanout in Decatur. Quote by email; text when ready. Confirm item volume before booking.
The work behind the interface.
Operational modeling
Customer, property, lead, quote, appointment, conversation, partner, and financial records form a connected operating model.
Intelligent workflows
Call transcription, coaching, drafting, marketing analysis, document work, and automation run through controlled workflows.
Multiple user contexts
Customers, office teams, field operators, partners, and owners each receive a purpose-built interface and permission boundary.
Provider integrations
Communication, advertising, calendar, payment, media, and AI providers connect through defined application boundaries.
Durable processing
Background work uses queued events, retries, scheduled tasks, and operational health signals instead of relying on fragile request chains.
Operational safeguards
Authentication, route permissions, feature gates, audit evidence, and explicit approvals govern higher-impact actions.
Let's build something useful.
Tell us what your organization is working toward. We'll help explore where intelligent software and automation could make a meaningful difference.