AI Partner Orchestration Platform

Overview#

Proprietary knowledge makes AI materially more useful. A generic language model knows nothing about an organisation's internal procedures, historical case patterns, or jurisdiction-specific regulatory guidance. The AI Partner Orchestration Platform changes that by combining conversation intelligence, private knowledge grounding, and multi-provider orchestration, so AI responses are anchored in verified internal data rather than general training knowledge.

Organisations ingest their own knowledge bases, manage stateful multi-turn conversations, and automatically route workloads across provider tiers to optimise cost and performance without sacrificing quality or maintaining separate integrations for each AI provider.

Key Features#

Conversation Management: Provides stateful, multi-turn conversation orchestration with automatic context persistence, token budget management, and metadata enrichment for investigation and case linkage.
Private Knowledge Grounding (BYOK): Ingest proprietary documents, policies, and datasets to ground AI responses in your organisation's verified information, dramatically improving relevance over generic AI outputs on domain-specific questions.
Smart Router: Automatically routes AI workloads to the most cost-effective provider tier based on task complexity, directing simple tasks to economical infrastructure while escalating complex reasoning to premium models.
Streaming Response Delivery: Real-time token-by-token response streaming improves perceived speed and user engagement for conversational interfaces.
Knowledge Source Management: Organises proprietary data into logical sources with granular access controls, versioning, deduplication, and activation states for multi-tenant isolation.
Analytics Observatory: Real-time visibility into performance, accuracy, cost, and usage patterns enables data-driven optimisation of AI operations.
Interactive Playground: Browser-based testing environment for prompt engineering, model comparison, and integration validation before production deployment.
Multi-Provider API Abstraction: Single interface abstracts the complexity of multiple AI providers, enabling provider-agnostic development with automatic retries and response normalisation.
Enterprise Security and Compliance: Multi-tenant architecture with organisation-scoped data isolation, cryptographic audit trails, and configurable data residency for regulatory compliance.

Use Cases#

Financial Crime Investigation Assistant: Ingest internal policies, regulatory guidance, and historical case reports to create a knowledge-grounded AI assistant that cuts investigation time while maintaining full audit trails of AI-assisted decisions. Financial crime units at banks and government agencies apply this to ensure AI recommendations stay within the boundaries of their compliance frameworks.
Multi-Language Customer Support: Deploy conversational AI with streaming responses and private knowledge grounding to handle high volumes of multilingual customer inquiries with automatic escalation for complex issues.
Legal Document Analysis: Combine premium-tier reasoning with ingested firm precedents and jurisdiction-specific case law for high-accuracy legal research at a fraction of traditional research costs.

Integration#

The platform integrates with existing application infrastructure through a flexible API layer supporting conversation management, knowledge ingestion, provider orchestration, and analytics. Enterprise onboarding typically requires only hours of configuration including authentication setup, knowledge ingestion, and production deployment.

Open Standards#

GraphQL (June 2018 specification): All conversation management, knowledge-base operations, provider orchestration, and real-time intelligence streaming are exposed through a GraphQL API with typed queries, mutations, and subscriptions.
OpenAI Chat Completions message schema: The platform adopts the de-facto industry message format (system/user/assistant role-and-content objects) as its normalised interchange model across every connected LLM provider, enabling provider-agnostic development.
OAuth 2.0 Bearer Token (RFC 6750): Outbound calls to AI provider REST APIs authenticate via HTTP Authorization Bearer headers; inbound API access is gated through the same bearer-token scheme enforced by the platform security layer.
IEEE cosine similarity / pgvector: Private knowledge grounding retrieves semantically relevant document chunks using cosine-distance vector search (the pgvector <=> operator) over 768-dimensional embeddings produced by BAAI BGE models.
FIPS PUB 180-4 SHA-256: Cryptographic audit provenance chains hash each operation's content with SHA-256 and link entries by previous-hash pointers, providing tamper-evident records of all AI-assisted decisions.
IANA MIME types (RFC 2046): Document ingestion validates and routes uploaded files by IANA-registered MIME type (application/pdf, application/vnd.openxmlformats-officedocument.*, text/csv, application/json, and others), with extension-and-MIME dual-verification to prevent bypass.
ISO 8601: All timestamps across conversation records, analytics windows, token-usage tracking, and knowledge-source metadata are serialised as ISO 8601 UTC strings.

Last Reviewed: 2026-02-05 Last Updated: 2026-04-14