Skip to main content
Research is the beginning, not the end. Every Project in DABAR can become an Autonomous Agent — a service that answers questions, executes workflows, and connects to your existing systems under the same policy governance as the research layer.

​
From Project to Agent

The lifecycle is simple:
  1. You build a Politic — the rules of reasoning.
  2. You run a Project — apply the politic to a body of sources.
  3. You deploy the project as an Agent — exposing it to users, systems, or other agents.
The agent doesn’t forget the rules. Every action it takes, every answer it gives, is still labeled CONFIRMED, NOT FOUND, or ESTIMATED and still cites its sources.

​
What agents can do

Agents go beyond Q&A. A DABAR agent can:
  • Answer grounded questions from your team or customers.
  • Analyze new inputs on demand — an incoming contract, a new application, a fresh data feed.
  • Act in external systems — open a ticket, update a record, send a notification, trigger a workflow.
  • Collaborate — hand off to other agents or escalate to a human when a rule demands it.

​
Connectivity

Agents connect outward through several transport layers:

MCP

Model Context Protocol — the standard way DABAR agents expose tools and consume tools from other systems.

REST APIs

Call any HTTP service your organization exposes, inside the VPC or over the public internet.

Custom skills

Package organization-specific logic as a reusable skill an agent can invoke.

Browser automation

Drive web interfaces that don’t expose APIs — scoped to the sites you allow.

​
Governance still applies

An agent is not a loophole around the Policy Engine. Every action an agent takes:
  • Is constrained by the politic it was deployed under.
  • Is logged with inputs, outputs, sources, and labels.
  • Can be suspended or rolled back by rotating the underlying politic.
This is why DABAR agents are safe to put in front of regulated workflows — the enforcement surface is the same whether the agent is answering a question or writing to a database.

​
Example: the credit committee

A bank deploys a Credit Risk Agent built from a politic that encodes its lending guidelines, grounded on the loan applications in the current batch. The committee queries it live:
“What’s the environmental risk profile for applicant 0142?”
The agent answers with labeled, cited findings. If the committee asks it to escalate, the agent opens a ticket in the bank’s internal system — still under the same politic, still with a full audit trail. The same agent, same politic, same sources — now driving a decision in real time.

​
Next

Deploy a project

Promote a draft project into a live agent.

Policy Engine

The rules every agent inherits from its politic.