AI-assisted workflows that ship to production, not to a demo.
AI inside intake, routing, and approvals, with humans on every critical decision.
/ Overview
Useful AI is not a chatbot bolted on the side. It is automation with judgment wired into the workflow, watched by a human, and accountable for what it does.
Argus connects to the CRMs, inboxes, and ops tools you already use. Agents read live context, take constrained actions, and route exceptions to people. Every run is logged, permissioned, and reviewable before it touches production data.
Request a demo/ At a glance
Less manual handling on routed work
80%
Actions logged and reviewable
100%
80%
Less manual handling on routed work
100%
Actions logged and reviewable
3x
Faster intake-to-resolution
1
Human approval layer where it counts
Agents that operate inside your systems.
Classify and route work the moment it arrives ↗
Emails, forms, documents, and chat sorted automatically.
Draft, update, and notify within clear limits ↗
Agents act only inside permissions you define.
Approvals and logs around every decision ↗
Confidence thresholds escalate the hard calls to people.
Connected to your tools, not stranded in a tab.
Argus reads from CRM, email, documents, and databases, then takes the next action in the same systems your team already uses. The result is a workflow that runs, not a copilot that suggests.
- CRM, email, docs, and database integrations
- Extraction, classification, and decision support
- Actions executed in your existing tools
Guardrails, logs, and a human in the loop.
Every agent run leaves a reviewable trail. Confidence thresholds, permission boundaries, and approval states make sure automation never crosses the lines you set.
- Permission boundaries per agent
- Confidence thresholds and escalation
- Full action logs and rollback
From a manual grind to an auditable workflow.
Map the workflow
Inputs, decisions, tools, exceptions, and current cost.
Design guardrails
Define what AI can decide, draft, and what needs a human.
Build & integrate
Wire agents to your systems with review states and logs.
Evaluate & tune
Test on real cases, fix failures, and set monitoring rules.
What teams ask about it
Is this just a chatbot?
No. Chat may be one interface, but the value is connected workflow execution inside your tools.
Can we keep humans in control?
Approval states, permission boundaries, and logs are part of every build.
What if the model is wrong?
Argus uses fallbacks, confidence thresholds, and review points around known failure modes.
