Workflow automation
Automation that is safe to leave running.
Most automation breaks quietly. Ours is built like infrastructure: every step idempotent, every failure retried and visible, every manual decision routed to a person with context. The result is work that moves on its own and a team that trusts it.
Start a project
- Temporal
- TypeScript
- Postgres
- Anthropic
- Kafka
- dbt
What it includes
- Durable workflows across your systems, with retries, timeouts and compensation
- AI steps for classification, extraction and drafting, with confidence thresholds
- Approval and exception queues for the decisions a person should make
- Monitoring, alerts and a timeline for every item that passed through
How it is built
- Idempotent connectors to your ERP, CRM, support desk and data warehouse
- Schema validation at every boundary so bad data stops early
- Replay tooling for reprocessing after an upstream fix
What you keep
- Workflow definitions and connectors as code in your repository
- A catalogue of every automation, its owner and its SLA
- Dashboards that show throughput, failures and time saved
Related
Often built together
- Enterprise AI agents
Agents that read, decide and act inside your systems, with evals, permissions and an audit trail from day one.
- Custom platforms
Multi-tenant platforms built to be operated: auth, billing hooks, admin, observability and documentation included.
- CRM engines
The customer record, pipeline and automation layer underneath your product, with AI scoring and enrichment built in.
Tell us what you need built.
A short brief, a real engineer reading it, and a scoped answer within a few business days.