Architecture Documentation For Technical Evaluators
This page provides a structured technical reference for the Ooumph USI platform. It covers the three-layer sovereign AI stack, the OSIE™ inference engine, deployment models, integration APIs, and security specifications.
Written for CTOs, security evaluators, and procurement officers conducting due diligence on institutional AI infrastructure.
Platform Overview
The Ooumph USI (Unified Sovereign Interface) platform is an institutional AI execution layer designed for regulated organisations that require full data sovereignty, auditability, and on-premise control.
The platform is structured around three distinct layers, each addressing a specific institutional requirement.
Coordinating all three layers is the OSIE (Ooumph Secure Inference Engine). It routes queries, executes inference, enforces access policies, and holds sub-100ms latency across production workloads.
This architecture is designed for deployment inside institutional data centres, air-gapped networks, and hybrid environments. It supports multi-tenant isolation, horizontal scaling, and compliance with the DPDP Act, GDPR, and RTI Act by default.
Architecture Layers
Infrastructure, intelligence, and trust. Each layer is separately auditable.
Federated Learning Model
The foundation layer. FLM ensures all model training and inference happen inside your institutional perimeter. Only federated gradient updates are exchanged, never raw data.
- On-premise model deployment with full institutional control over weights, data, and update cycles
- Air-gapped operation mode for classified environments requiring complete network isolation
- Only federated gradient updates leave the local node, at any stage of training
- Sovereignty is a property of where the compute runs, and is verifiable at audit
Federated Thinking Model
The intelligence layer. Several specialised SLMs work the same problem in parallel, each tuned to a specific institutional function. Where their outputs conflict, the applicable statute decides rather than a majority vote.
- Specialised Small Language Models (SLMs) fine-tuned for departmental functions and domain vocabulary
- Context-aware reasoning that respects institutional rules, exceptions, and procedural hierarchies
- Deterministic reconciliation by statutory precedence wherever specialised models disagree
- Low-latency edge inference for real-time operational decisions in field and office environments
Blockchain Audit Layer
The trust layer. Every AI interaction generates an immutable audit entry. Entries are cryptographically chained via SHA-256, making any tampering computationally detectable.
- Immutable chronological record of every AI query, inference output, and operator action
- Each entry is cryptographically linked to its predecessor by SHA-256 hash chaining
- RTI-compliant documentation structured for Section 4 disclosure requirements
- Legal defensibility for AI-assisted determinations in judicial and administrative proceedings
OSIE Inference Engine
The component that executes what the three layers specify: query routing, model execution, policy enforcement, and audit generation. The figures below are measured under production load.
Performance
Measured at national-scale institutional load.
- Sub-100ms latency (p95) for citizen-facing services
- Horizontal auto-scaling handles peak demand without operator intervention
- Concurrent execution of multiple models across departmental workloads
- Edge deployment for offline, remote, and bandwidth-constrained sites
- 99.99% uptime target on production deployments
Security
Applied from the model weights through to the network boundary.
- AES-256 at rest and TLS 1.3 in transit, applied to model weights and inference data
- HSM-backed cryptographic key management
- Role-Based Access Control enforced on every API endpoint and data path
- Network microsegmentation between tenants, modules, and services
- Continuous monitoring, with real-time alerting into your incident response workflow
Deployment Models
Four configurations. Choose by security posture and by what your operations team can realistically carry.
On-Premise
- •Complete platform installation in your data centre
- •All inference, training, and storage under institutional control
- •Updates managed on your schedule via authenticated packages
- •Assumes an infrastructure team is already in place
Air-Gapped
- •Zero external network connectivity at any point
- •Updates delivered via authenticated offline media
- •Full operational capability, including defence-grade workloads, without internet access
Hybrid
- •Sensitive workloads processed on-premise
- •Scalable workloads routed to approved cloud
- •Policy-based routing decides placement automatically
- •Suits institutions with mixed sensitivity levels
Managed
- •Ooumph operates the platform under strict SLA
- •No dedicated infrastructure team required
- •Monitoring, updates, and scaling handled by Ooumph
- •The fastest route to a production deployment
- •Exit path to on-premise remains open
Integration & APIs
The platform exposes a full API surface for integration with existing institutional systems, custom module development, and automated workflows.
API & Integration Capabilities
- RESTful API layer with versioned endpoints, rate limiting, and structured error responses
- Webhooks fire on inference completion, alerts, and status changes
- RBAC-governed API access, scoped per endpoint and logged
- Multi-tenant isolation enforced at the API, database, and network layers
- An SDK for departmental module development, with typed interfaces and local testing
Technical Specifications
Key technical parameters for procurement review and security evaluation.
| Parameter | Specification |
|---|---|
| Encryption | AES-256 at rest, TLS 1.3 in transit |
| Authentication | RBAC with HSM-backed key management |
| Inference Latency | Sub-100ms (p95) |
| Uptime target | 99.99% for production environments |
| Compliance | DPDP Act, GDPR, RTI Act |
| Deployment | On-premise, Air-gapped, Hybrid, Managed |
| Audit Trail | SHA-256 hash-chained blockchain ledger |
| Model Isolation | Per-tenant model weights and inference contexts |
Ready for a Technical Review?
Bring your security and compliance questions. We will send documentation scoped to what your evaluation actually needs to cover.
Or contact us directly at info@ooumph.com