Captured from real work.
Approved by named owners.
Versioned and audited.
Routed to the optimal execution engine.
Available to people in chat.
Your team tried AI. It gets things almost right. In teams like finance and operations, that still gets redone by hand.
The gap is not the model. It is context: the exceptions, the rules, the calls that live only in people's heads. Diligent4 captures it.
One approved version of every procedure, with an owner and a history, ready for any AI or automation to run.
Share your screen and talk through the task. Recordings, documents, and agent feedback all feed the same engine.
Five people do a task five ways. Review, approve, and publish the one official version, with a named owner and a full history.
A recording is a draft. The procedure is what you approved.
Any agent, bot, or script runs the approved version, served over MCP. Change it once and every execution updates.
The layer between a demo and a deployment. What a procedure goes through before an agent is allowed to run it.
Nothing becomes official until a named owner approves it.
Every procedure has a history. Every change is a reviewed diff.
Org-scoped RBAC synced to your identity provider. Retrieval respects permissions too.
Who approved what, when, and exactly which version the agent executed.
Served over MCP. Claude, OpenAI, Copilot, or your RPA stack are interchangeable parts, not lock-in.
Procedures are not only for agents and automation teams. Employees get the right information at the right time: the conditionals, the thresholds, the how-tos.
In production at regulated financial institutions. Every deployment passed CISO review. Full overview under NDA.
A 7-hour reconciliation at one of Israel's largest investment houses now runs in 4 minutes. Zero errors, following the approved procedure.

Most runs finish in one shot, even complex ones.

Fewer errors overall, and no severe errors in our tests.
Real workflows, recorded in the product. Pick a demo and share the link.
Narrate a task. Explain your logic. Minutes later an agent runs it your way.
Not a recording. Not a prompt buried in someone's chat.
Approved playbooks replace ad-hoc prompts. One golden standard, not 20 versions across employees and interns.
Agents need less context and fewer retries. Deterministic steps run as cheap scripts, not expensive LLM calls.
The system recommends how to run each task: AI agent, RPA, or script. Not everything is AI-ready or RPA-suitable.
Recordings, documents, and agent runs enrich one corpus. Every capture makes the next workflow closer to done.
One recording pays off in four directions.
A ready-to-build project for each workflow, plus a ranked backlog. Diligent4 flags what is AI-ready, RPA-suitable, or best kept manual.
Capture your work once and hand the busywork to an agent. Faster onboarding, cleaner handoffs.
One source of truth for how work happens. Govern the rollout and enforce one standard.
Where almost right is unacceptable. AI runs close, reconciliations, and approvals to your standard.
Finance and ops are the sharpest fit. Any high-stakes, repetitive process works.
Manual allocation across systems. Days of work.
AI follows your allocation logic. Days become hours.
Manual matching. Exceptions handled ad hoc.
AI matches by your rules and flags only true exceptions.
Manual validation of quotes against contracts.
AI checks your contract terms and approval thresholds.
Analysts rebuild the same reports each cycle.
AI repeats your analyst's exact method every time.
Procedures buried in old PDFs.
Living procedures the AI follows and evidences.
Bring one painful process. In 30 minutes we capture it and your AI runs it.