Three surfaces, one system of record.
Everything a real pipeline needs, in one system.
Work Inbox
A prioritized queue of approvals, forms, and decisions across every pipeline you run.
Workflow Studio
Visual, drag-and-drop pipeline builder with validation, sandbox testing, and version control.
AI Task Agents
Purpose-built agents handle extraction, compliance checks, document generation, and API calls.
Human-in-the-Loop Approvals
Approval, form, and decision gates pause the pipeline and route to the right person automatically.
Live Monitor & Analytics
Real-time run status, bottleneck detection, and pipeline-level performance analytics.
Stakeholder Portal
Secure, OTP-protected portal for external stakeholders to upload files and track status.
Audit Trail & Compliance
Full audit logs, status history, and output records for every run — captured, not reconstructed.
Agent Builder
New automation is generated, tested, and verified in a sandbox before it’s trusted with real work.
Sovereign Architecture.
Built on a secure, containerized infrastructure that isolates data and ensures a verifiable execution trail for every action.
Input Layer
Ingest structured and unstructured data via API, upload, or direct integration.
Cognitive Engine
LLM-driven nodes interpret intent and route each step to the right logic path — code decides what’s possible; the model chooses only among valid options.
Execution Nodes
Containerized, sandboxed agents execute each action in isolation — no shared credentials, no shared blast radius.
Verification Loop
Every output is checked against its expected schema and logged to an immutable audit trail before the run continues.
Plain English in. A structured workflow out.
Studio turns a description into a series of steps, each containing sub-steps: a form to fill, data to extract, a document to generate, an approval, a decision gate, an API call, a notification.
"When a new hire is confirmed, collect their details, verify eligibility against policy, generate the contract, get the hiring manager to sign off, then create their HR and IT accounts and notify the team."
A live workflow graph, checkpointed as it moves.
An orchestrator decides which step runs next; a step supervisor picks the next sub-step; specialized agents carry out each unit of work. State is checkpointed continuously, so a run survives a restart and picks up exactly where it left off.
How is AI kept trustworthy?
The judgment stays with AI; the decisions are computed in code. Change the input and watch the branch change — the same input always gives the same answer.
Over the $200 threshold, so the gate escalates — every time, for every identical input.
Where do people stay in control?
Automation runs autonomously until it reaches a decision point. Then it pauses, hands off a clear brief, and waits. Make the call below.
A real decision has been reached
The approval agent prepared a decision brief with the underlying data. The run holds its state and waits — it will not fabricate a result to keep moving.
Captured, not reconstructed.
Every status change, approval, decision, input, and output is logged as it happens, at the step level, into a durable system of record.
Per-step audit trail and RBAC land in R1; exportable, tamper-evident audit in R1.1.
Human corrections become system improvement.
Every human override and correction is captured. Over time Atagente surfaces patterns, suggests workflow edits, and raises its own automation confidence.
Everything a real pipeline needs, in one system.
What the platform delivers today, grouped by theme. Items still hardening in the current MVP cycle are noted on the roadmap.
AI workflow authoring (Studio)
Agentic execution engine
Human-in-the-loop control
Trust & correctness
Work management & oversight
Knowledge & connectivity
Platform, security & tenancy
External collaboration
See it run on one of your own processes.
Bring us one real workflow — we'll take it from plain English to a monitored run.