Shared agentsArtificial Intelligence
AI runs inside business processes governed by an orchestration layer, which decides when an AI task runs, what data it sees, and where a person reviews the result.
- AI & Intelligent Platforms
//Agentic Case Platform
Governed AI agentorchestration.
The case is the harness: it decides what an agent may do. The agent decides what to do next. You stay in control of both.
Reliability
Most of the time is not good enough
When agents act on real customers and money, “usually right” is a liability. The case sets the boundaries.
Context
Rent the intelligence, own the context
Everyone rents the same models. Your processes, data, rules, and history are what make it yours.
Orchestration
Scoped context, full audit
Each agent gets only the slice of the case it needs, and every call is on the record.
//Overview
What is an agentic case platform?
An agentic case platform is case management software that orchestrates AI agents, people and systems on the same case. The case defines what an agent may do; the agent decides what to do next; people stay in control of both.
DataObserve Flow is an agentic case platform built on a full case and process engine: processes and cases, rules and decisions, integrations, events, human work and documents. Agents get scoped context and every action is audited.
//How it works
The caseis the harness.
Step 1
Start with a case
An onboarding, a claim, a loan application: stages, rules, and a clear goal.
//A full case platform underneath
Not just agents. A full case platform underneath.
Processes & cases
BPMN processes and CMMN cases for long-running work.
Rules & decisions
DMN decision tables for calls that must be deterministic.
Integrations
REST and service connectors to your core systems.
Events & messaging
Message-broker events start and steer cases.
Human work
Tasks, forms, and role-based assignment.
Documents & content
Documents, templates, and generated output with the work.
//Explore more withDataObserve
More from Flow · AI & Intelligent Platforms
Agentic AI
Enterprise AI agents are outcome driven: from task automation to proactive decisions and goal pursuit, acting independently within clearly defined boundaries.
- AI & Intelligent Platforms
Case Management
Automation, orchestration, and human decision-making combined, to adapt to unpredictable tasks and decisions over the life of a case.
- Case & Process Management
Process Orchestration
Encode and enforce the end-to-end process, so the business can evolve fast at minimal cost, with long-running automations for routine and exception-driven work.
- Case & Process Management
//Principles
Rent the intelligence, own the context
Don't burn tokens on deterministic work
If the same input always gives the same output, model it, don't prompt it.
Codify business knowledge
Into human-readable, auditable artifacts. An automated process is an asset.
Durable and model-neutral
State, transactions, and retries built in; swap the LLM and keep the logic.
//FAQs
Agentic Case Platform: questions teams ask
Why use a case platform for AI agents?
A case holds the context, rules and history for a piece of work. Using it as the agent's harness keeps agents scoped, durable and auditable.
Is DataObserve Flow tied to one LLM?
No. The platform is model-neutral, so you can swap the language model and keep your process logic, state and audit trail.
What does 'rent the intelligence, own the context' mean?
Models can be swapped as they improve, but your processes, rules and case data are lasting assets you own and control.
When should work not use an AI agent?
When the same input always gives the same output. Deterministic work is cheaper and safer as a modelled process or decision table.
