API-First Proposal: GPT-5 Integrated Retrieval for Adamet Pvt Ltd

Enhance GPT-5 with multi-source enterprise APIs. Private, provenance-tracked, policy-enforced. No new UI required. Tailored solution for Adamet's business intelligence needs.

SharePoint Connector
Tender DB
Policy Engine
RAG Orchestrator
Citation Mapping

Client Requirements

Exact needs driving this API-first architecture

API-First Architecture

Integrate multiple internal data sources into GPT-5 tools under strict privacy controls.

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Acceptance Criteria

  • All data access via RESTful APIs with JWT authentication
  • GPT-5 calls tool facade; no direct database access
  • Zero model training on proprietary data
  • Support for future connector additions without code changes
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Multi-Source Integration

Seamlessly connect SharePoint, Tender DB, and competitor data with unified retrieval.

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Acceptance Criteria

  • Pluggable connector architecture for each data source
  • Unified response format across all sources
  • Parallel query execution with result fusion
  • Source-specific authorization checks
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Privacy & Compliance First

Enforce ABAC/RBAC policies and redaction before any payload reaches GPT-5.

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Acceptance Criteria

  • Policy engine filters unauthorized chunks pre-retrieval
  • Row-level and document-level access control
  • PII/sensitive data redaction in payloads
  • Full audit trail with compliance logging
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Deterministic Provenance

Every response includes durable citations with doc_id, record_id, source URI, and checksum.

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Acceptance Criteria

  • Citation mappings stored in provenance store
  • Timestamped retrieval traces
  • Immutable citation URIs for audit
  • Human-readable source attribution in responses
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No New End-User UI

Users interact only with existing GPT-5 interface; all complexity hidden behind tool calls.

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Acceptance Criteria

  • Zero changes to end-user chat experience
  • Tool invocation transparent to users
  • Response format identical to standard GPT-5
  • Admin dashboards for ops/analytics only
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Our Solution Architecture

Six core pillars that deliver secure, scalable, and auditable AI integration

1. API Gateway / Tool Facade

GPT-5 Enterprise calls our secure API Gateway, which presents tools like fetch_tenders, search_docs, and fetch_competitors. All requests authenticated via JWT/OIDC.

2. RAG Orchestrator

Plans multi-source queries, orchestrates semantic and keyword searches, fuses results, and assembles context with citations before returning to GPT-5.

3. Policy Before Payload

Policy Engine enforces ABAC/RBAC and redacts unauthorized chunks. Only compliant, filtered data reaches the model.

4. Pluggable Connectors

Modular adapters for SharePoint, Tender DB, Competitor DB, and future sources. Each connector handles authentication, schema mapping, and retrieval.

5. Provenance Store

Durably maps every retrieved chunk to its source (doc_id, URI, checksum, timestamp). Enables citation verification and audit trails.

6. Observability & Audit

Logs, metrics, and traces for every query. Policy audits, latency SLOs, and retrieval analytics in one dashboard.

High-Level Architecture

API-first design with GPT-5 Enterprise as the consumer. All components enforce access control and redaction before returning payloads.

Identity Provider (SSO/RBAC) authenticates all requests

API Gateway exposes tools to GPT-5 with normalized query/plan interface

RAG Orchestrator performs semantic + keyword search, filters via Policy Engine

Connectors retrieve from SharePoint, Tender DB, Competitor DB

Provenance Store maps citations; Observability tracks all operations

Security & Compliance

No Model Training

Zero proprietary data used for fine-tuning or model updates

ABAC/RBAC

Attribute and role-based access control enforced before retrieval

Redaction

PII and sensitive fields masked in all payloads to GPT-5

Private Networking

All internal APIs on private VPC with zero public exposure

Audit & Telemetry

Full trace logs with policy decisions and retrieval lineage

Deliverables & Timeline

1

Discovery & Design

2 weeks
  • Finalize connector schemas
  • Define tool signatures for GPT-5
  • Security policy framework
2

PoC Development

4 weeks
  • SharePoint + Tender DB connectors
  • RAG orchestrator with policy engine
  • 12-15 test queries with success metrics
3

Testing & Validation

2 weeks
  • Latency benchmarks (p95 < target)
  • Provenance verification tests
  • Security audit report
4

Production Rollout

2 weeks
  • Live integration with GPT-5 Enterprise
  • Observability dashboards
  • Runbook and ops handoff
95
p95 < 2s
Query Latency
99.9
%
Connector Uptime
15
queries
Test Queries

Multi-Source Query Sequence

Step-by-step flow: User asks GPT-5 → Tool call → Policy check → Multi-source retrieval → Citation assembly → Final answer with provenance.

Download Complete Proposal

Get the full proposal document with detailed architecture diagrams, timeline, and technical specifications for Adamet Pvt Ltd.

Questions? Contact our team