AI Automation

Replacebusyworkwithtraceableautomation

AI-assisted workflows that run across your tools, handle judgement calls responsibly, and leave an audit trail your team can actually follow.

See pricing
Workflow
Signal to action in seconds
Live
Trigger · classify · route · notify
0
%
Manual steps eliminated
0
x
Faster than a Zap chain
0
+
Integrations supported
0
%
Runs logged and replayable
Automation capabilities

Workflows that survive contact with production

Trigger, decide, act. Everything logged, everything replayable, everything owned by the same pod that built it.

Workflow design

Map the process first, automate second. We refuse to automate bad processes, because that just makes the bad process faster.

AI-assisted decisioning

Classify, route, extract, and summarise with models inside the workflow. Deterministic outcomes for deterministic steps, AI where judgement is needed.

Event-driven triggers

Webhooks, schedules, database changes, inbox rules. Start workflows where work actually originates.

Integration breadth

CRM, billing, ticketing, warehouse, comms. We wire into what you use and document every integration we own.

Human approvals

Approval steps for high-impact branches. Slack, email, or inline UI. People stay in the loop where it matters.

Observability and replay

Every run logged, every step replayable. Debug and improve with evidence, not anecdotes.

What we automate

Workflows worth taking off your team

Customer onboarding

Extract data from inbound forms and emails, enrich, create accounts, brief the team. A smooth first hour, every time.

Lead qualification

Route, score, and enrich inbound leads. Sales gets context, ops gets clean data, nobody writes the same summary twice.

Invoice and document processing

Classify, extract, match, and post. AI reads what rules cannot and hands back confidence scores you can act on.

Incident triage

Classify incoming alerts, assemble runbooks, and nudge the right responder. Faster resolution, fewer pages.

Rollout

Audit first, automate second

01

Process audit

Week 1

Shadow the workflow, quantify the time and error cost, and decide where automation earns its keep.

02

Design and sign-off

Week 1 to 2

Whiteboard the target workflow with the people who run it today. No surprises on rollout day.

03

Build and integrate

Week 2 to 5

Implement on your infrastructure with typed integrations and AI steps where decisioning adds value.

04

Parallel run and rollout

Week 4 to 6

Run old and new in parallel. Cut over only once results match and the team trusts the automation.

Stack

Orchestration, AI, and integrations

Orchestration
TemporalInngestTrigger.devn8nWindmill
AI steps
OpenAIAnthropicGeminiOpen-weight models
Integrations
HubSpotSalesforceSlackStripeIntercomSnowflake
Runtime
AWSGCPAzureCloudflare WorkersVercel
FAQ

Automation questions

Those are fine for 20-step automations with predictable shapes. We build long-lived, branching, AI-aware workflows that need versioning, tests, and observability.

Yes. Most engagements begin with one high-pain workflow. Once that is humming, we stack on adjacent ones.

Your cloud. Your credentials. We do not run your workflows on our infrastructure unless you explicitly ask us to.

Retries, circuit breakers, and dead-letter queues. When a third-party integration breaks, the workflow does not.

Every workflow ships with a diagram, a plain-English description, and a runbook. Handover is a design goal, not an afterthought.

Start a Discovery Call

Ready to ship

faster than you can hire?

30 minutes to scope, stack, and a first-sprint plan. No pitch deck, no pressure.