AI that acts inside your process with explicit rules: traceability of every decision, configurable confidence thresholds, human validation when needed and exportable audit. No black box.
Each one performs a concrete role inside the process — not generic intelligence.
Assisted workflow generation from a natural-language description. You review and validate the model before deploying.
Use cases: fast project bootstrap, process prototyping, converting manuals into workflows.
Document classification, extraction and validation with per-field confidence. If confidence drops below the threshold, it escalates to a human.
Use cases: invoices, contracts, case files, supporting documents, scanned forms.
Resolves standard cases inside defined rules. Exceptions, outliers and unprecedented cases go to a human for review.
Use cases: routine expense approval, policy validation, request triage.
Coordinates several agents and services inside a long process: case state, observability and retries governed by BPMN rules.
Use cases: multi-step customer onboarding, complex case files, supplier approval cycle.
Five layers of control that prevent "unsupervised autonomous AI".
For each task type you define from what certainty level the agent acts alone. Below that, it automatically escalates to a human reviewer.
The agent only accesses documents, data and APIs explicitly authorised. No "agent with access to everything": principle of least privilege.
Every action records: input, model and version, reasoning, sources consulted, output and human validation if any. All exportable.
Processing in European data centres by default, no international transfer without explicit contract. Personal data can be pseudonymised before reaching external LLMs.
Any agent action can be reverted or rejected by an authorised user. Critical decisions are always finally signed off by a person.
The terms you'll see in agentic AI for BPM.
Coordination of several AI agents and services inside a long process with governance, observability and human-in-the-loop.
Pattern where a human validates, corrects or approves agent decisions when a confidence threshold is crossed or an exception occurs.
Analysis on process logs to detect bottlenecks, deviations and improvement opportunities. Dokuflex offers it as SLA dashboards and metrics.
Intelligent reading, classification and extraction of documents with OCR + AI. With agents and HITL it's called agentic IDP.
Protocols for interoperation between agents and AI services. Help one agent invoke another or query an external tool with explicit contract.
AI agent output with its reasoning, sources and full log, exportable for internal, regulatory or post-incident audit.
An AI system that acts inside a business process with explicit rules: configurable autonomy levels, decision traceability, human validation when required and exportable audit.
An assistant or chatbot answers questions. An AI agent takes actions inside a process: classifies documents, extracts data, proposes decisions, escalates exceptions.
A human validates, corrects or approves the agent's decision when a confidence threshold is crossed or an exception occurs. You define when the agent acts alone and when it escalates.
Every action records: input, model and version, reasoning, sources, output and human validation if any. The full log is exportable.
Coordination of several AI agents and services within a process with state governance, observability and HITL. In Dokuflex, orchestration sits inside the BPM engine.
Bring a real case (invoice, contract, case file) and we design the agent with you: rules, confidence thresholds and human validation.