AI ERP with agents inside the systems you run
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LLM.coPrivate, self-hosted LLM deployments
Legal AI infrastructure for firms
AI RFP discovery and response drafting
Automatic.coBusiness process automation
CyberAttack.aiThreat detection and defense
Secure AI virtual data roomsAutomate the work, not the demo.
We design and deploy AI workflows that complete real operational tasks — with observability, human-in-the-loop checkpoints, and graceful failure modes. Not Zapier-with-an-LLM.
Most of your team's work isn't the work.
Every operations leader has the same complaint: their team spends 30–60% of every week on tasks that could be automated, should be automated, and aren't — because the workflow is too custom for Zapier and too 'in-between' to make the engineering roadmap.
That's the automation tax. It compounds, it scales with headcount, and it's the cheapest thing to fix if you fix it properly.
Workflows we've shipped, by department.
Lead enrichment & routing
Inbound enrichment, outbound research, CRM hygiene, meeting-prep briefs.
Triage & deflection
Tier-1 resolution, ticket routing, history summarization, after-hours voice agents.
Data shuffling, gone
ETL between SaaS tools, invoice processing, internal knowledge Q&A, onboarding.
Reconciliation & reporting
Bank-to-ledger reconciliation, expense categorization, recurring reports with anomaly detection.
Content & attribution
Brief generation, audience research, cross-channel attribution with explanations.
Built to be trusted
Retries, circuit breakers, confidence thresholds, audit logs, dashboards your ops lead can read.
Humans in the loop, by design.
“Fully autonomous” is rarely the goal. The right question is where a human's judgment justifies their cost.
| High stakes | Low stakes | |
|---|---|---|
| High reversibility | Mandatory human approval (send email, issue refund) | Auto with notification (tag a ticket, update CRM) |
| Low reversibility | Block + escalate (delete record, cancel subscription) | Auto + audit log (forecast, run a report, summarize) |
What automation should cost — and return.
A real worked example: customer-support tier-1 deflection.
4,200 tier-1 tickets/month. 30% fully auto-resolved, 60% pre-summarized for a human. Average handle time 11 min → 6 min. That's ~290 FTE-equivalent hours saved per month — about 3,480 hours/year.
At a $42 loaded cost per FTE hour, that's ~$146,160 in labor capacity freed each year — the figure a build and its running costs are measured against when the workflow is scoped.
How automation projects engage with us.
- Process inventory + ROI sizing
- Tool/stack recommendation
- Prioritized 12-month roadmap
- Process design + golden dataset
- Orchestration + AI-decision steps + evals
- Integrations, dashboards, shadow rollout
- Eval-set expansion + threshold tuning
- Model migrations + new workflows
- On-call + monthly ROI reports
Common questions.
What's a good first workflow to automate?
Will this replace my team?
How do you measure ROI?
What integrates with our stack?
Is this different from Zapier?
How is this different from agents?
Related reading
The plumbing that lets a workflow actually touch your systems.
Tell us where the hours are going.
A 30-minute call. Bring the process that's costing you the most time. We'll size what automating it actually looks like — and tell you honestly if the ROI is there.