RAG + API
Powered by Decidian

Turn enterprise knowledge into decision intelligence.

Build a new governed RAG core, enhance an existing retrieval system, or embed decision intelligence into enterprise workflows through API integration.

POST /v1/decide
{
  "workflow": "vendor_risk_review",
  "sources": ["rag://legal", "rag://vendors"],
  "governance": { "human_review": true }
}
→ decision_packet.pdf200 OK · 1.2s
L01
Client Systems
Internal appsDashboardsAI systemsDiligence toolsPartner productsLLM applications
L02
Sources
Existing RAGDocumentsVector storesData roomsGRCSIEM/SOARLLM apps
L03
Decidian Intelligence
Evidence bandingSource reliabilityProvenanceActor simulationScenario branchingRed-team assuranceAudit exportDecision packets
L04
Outputs
Decision packetsRisk heatmapsScenario branchesAudit replayAPI responsesMonitoring signals
Why Ordinary RAG Is Not Enough

Retrieval is necessary. It is not sufficient.

Generic RAG can answer questions. It cannot grade evidence, simulate stakeholders, or produce a decision packet you can defend in a board room.

Retrieval without judgment
Weak source ranking
No evidence hierarchy
No scenario awareness
No actor context
No audit replay
No red-team testing
No decision packet output
No compliance boundary
No post-event learning
What Decidian Adds to RAG

Decidian Intelligence on top of retrieval.

Evidence bands
Source provenance
Source reliability scoring
Query fingerprints
Retrieval evaluation
Contradiction detection
Red-team retrieval testing
Decision-output gating
Actor-aware retrieval
Scenario-aware retrieval
Compliance context
Audit replay
Monitoring and calibration
Evidence Bands

P0 to P5 — uncertainty made legible.

Every material source, claim, inference, and output is assigned a public-facing evidence status based on source strength, freshness, provenance, decision relevance, and validation needs.

P0
Authoritative
Filings, primary regulators, contracts of record
P1
Primary
First-party operational records
P2
Verified secondary
Independent corroborated reporting
P3
Contextual
Strong contextual references
P4
Weak signal
Unverified signals
P5
Hypothesis
Assumption or working hypothesis
RAG Creation Workflow

A governed knowledge core in ten steps.

From source discovery to monitoring and calibration, every step is defined, evaluated, and handed off with documentation.

01

Source Discovery

Identify enterprise documents, contracts, filings, logs, policies, data rooms, tickets, research, and structured databases.

02

Knowledge Architecture

Organize by domain, sensitivity, access rights, freshness, jurisdiction, business function, and decision relevance.

03

Connector Strategy

Connect approved repositories, databases, APIs, file systems, SaaS tools, data rooms, and external feeds.

04

Chunking & Metadata

Prepare content with chunking, metadata, temporal markers, source hierarchy, access rules, and provenance tags.

05

Embedding & Vector Store

Deploy or configure pgvector, Pinecone, Weaviate, Elasticsearch, OpenSearch, or your enterprise-standard system.

06

Retrieval Evaluation

Test recall, precision, grounding, source ranking, latency, freshness, contradiction handling, and answer utility.

07

Evidence Banding

Classify sources by strength, admissibility, provenance, confidence, freshness, and decision relevance.

08

Governance & Review

Add access controls, logging, injection testing, output review, human escalation, and policy boundaries.

09

Simulation Integration

Connect retrieval to actor maps, scenario branches, red-team shocks, decision packets, and API outputs.

10

Monitoring & Calibration

Track retrieval drift, stale content, source conflicts, failed queries, user feedback, and post-event learning.

Existing RAG Enhancement

Make the RAG you already run defensible.

Decidian layers on top of your existing stack — no rip-and-replace — and adds the assurance, evidence, and audit properties your reviewers expect.

Before

RAG retrieves and summarizes.

DocsVector DBLLMAnswer
After Decidian

Grades. Challenges. Simulates. Packages. Audits.

SourcesProvenanceEvidenceSource gradeSimulateRed-teamPacketReplay
Current RAG problem
Decidian upgrade
Client result
Hallucinated answer
Evidence-banded output gating
Fewer unsupported conclusions
Weak source hierarchy
Source reliability scoring
Stronger enterprise confidence
No source lineage
Query fingerprints + replay logs
Audit-ready retrieval
Source conflicts
Contradiction detection
Explicit unresolved-issue register
Stale content
Freshness scoring + monitoring
Reduced content drift
Injection risk
Red-team retrieval testing
Safer retrieval workflow
No decision context
Actor- and scenario-aware retrieval
More useful outputs
No executive deliverable
Decision packet generation
Board-ready synthesis
API Categories

Ten public-safe API surfaces.

Endpoint names are illustrative. Authentication, payload schemas, and per-tenant configuration are documented per engagement.

Integration Patterns

Eleven ways to embed Decidian into the systems you already run.

01
REST API
02
Private VPC
03
On-premise
04
Managed service
05
SIEM / SOAR
06
GRC
07
Data room
08
Vector database
09
LLM application
10
Enterprise dashboard
11
Partner SaaS embedding
Reference shape

Endpoints and example response.

Illustrative endpoints
POST /v1/scenarios/run
POST /v1/actors/map
POST /v1/evidence/grade
POST /v1/branches/expand
POST /v1/redteam/shocks
GET  /v1/packets/:id
GET  /v1/audit/replay/:id
POST /v1/rag/assure
POST /v1/monitoring/subscribe
Example response
{
  "packet_id": "DCN-2031.07",
  "actors": 18,
  "branches": 6,
  "evidence_bands": { "P0": 12, "P1": 18, "P2": 9 },
  "shocks": ["regulator", "activist", "leak"],
  "confidence": 0.72,
  "audit_replay": true
}
API access, source connectors, and RAG topology are configured per engagement. Decidian does not disclose proprietary retrieval models, scoring weights, orchestration architecture, or internal workflow logic.
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