Approvals and exceptions
Classify the routine, route the unusual to a person with the context attached.
AI Automation
Automate your workflows
with AI agents.
Replace repetitive, manual processes with intelligent automation pipelines. We build LLM-driven agents that connect your tools, process data, and take action — reliably and at scale.
What we deliver
- LLM agents that plan, execute, and loop on real tasks
- Integrations with CRMs, ERPs, Slack, email, and databases
- Document processing and data extraction pipelines
- Trigger-based and scheduled automation flows
- Human-in-the-loop approvals where needed
- Observability dashboard with run logs and alerts
Workflows worth automating first
Inbox and ticket triage
Sort, enrich and assign incoming work before anyone opens it.
Data entry between systems
Move structured data across tools that were never designed to talk.
Reporting and reconciliation
Assemble the recurring report, flag what does not match.
Related reading
FAQ
Frequently asked questions
- What kind of workflows are a good fit for AI automation?
- High-volume, rule-heavy work where the input is messy but the decision is well understood — triage, classification, extraction, routing. Workflows nobody can describe precisely are a poor fit until the process itself is mapped.
- Will the AI make decisions without oversight?
- Only where you decide it should. Read-only steps can run autonomously; anything that spends money, messages a customer or is irreversible should require confirmation until production traces earn it wider latitude.
- How do you measure whether automation is working?
- Against an evaluation set defined before launch, plus production tracing on every run. Without both, you cannot tell whether a change improved things or broke something quietly.
- What happens when the model gets it wrong?
- The system should notice, contain the error and escalate — which means guardrails in deterministic code, audit logs and an undo path. That design work is most of what separates a demo from production.
- Do you replace tools like Zapier or n8n?
- Often we complement them. Deterministic glue is fine where it works; we add AI where the input is unstructured or the decision needs judgement, and keep the rest as ordinary code.