Research that can be inspected, challenged, approved, and shipped.
Deep Research Assistant turns a vague research request into a bounded workflow with explicit scope, question graphs, evidence fragments, claim records, approval gates, and a final report that can be reviewed like engineering output instead of chat history.
Assess enterprise controls for an AI research runtime.
review_first
Immutable excerpts with source and question linkage.
Atomic, qualified, and attached to evidence ids.
Scope, plan, outline, and publication gates.
Report draft plus progress, graph, events, and exports.
Most “research agents” produce prose. This one produces inspectable work products.
Every material statement should trace back to evidence, not prompt theater.
Technical reviews, architecture analysis, governance-heavy research, and decision support.
Everything important in the workflow is first-class.
Evidence-first pipeline
Intent becomes scope, perspectives, questions, search plans, evidence fragments, claims, contradictions, drafts, verification findings, and report output. The workflow is explicit at every stage.
Bounded multi-agent design
Research Director, Evidence Curator, Claim Builder, Verifier, Moderator, and supporting agents each have narrow responsibilities instead of sharing one opaque prompt.
Approval-aware operation
Review gates are built into the graph, not bolted on later. Runs can pause at semantic boundaries before scope expansion, outline approval, or publication.
Routeable API surface
The service exposes create/get run endpoints plus graph, frontier, progress, events, concept map, approvals, interventions, and exports for integration into real systems.
Deterministic validation
Route contracts, workflow behavior, and quality gates run in normal CI. Live Gemini checks stay opt-in and bounded so cost and flake do not leak into every push.
Enterprise control plane
Identity propagation, policy checks, source filtering, budget accounting, telemetry, and append-only audit events are all part of the system design.
From broad prompt to reviewable artifact.
Built to plug into product and ops surfaces, not just demos.
The project already documents and tests the API endpoints that matter for orchestration: run creation, run retrieval, graph inspection, frontier visibility, event replay, approval state, interventions, and export.
See the documented routes →/v1/research-runs/v1/research-runs/{run_id}/graph /frontier /progress/events /concept-map/interventions /exports/approvalsIt advertises rigor, not just autonomy.
Deep Research Assistant
- Claims are explicit records
- Evidence stays immutable
- Workflow events are inspectable
- Approvals are modeled in the graph
- Validation is split between deterministic and live tiers
Typical agent demos
- Prompt in, prose out
- Weak traceability to sources
- Little state visibility
- Governance handled outside the workflow
- Live dependencies mixed into normal CI