Live Execution Proofs, Not Slide Decks
Below are four deterministic and agentic AI systems written for Indian government and enterprise institutions, each running under the constraints its department actually operates within.
All four run on the Sovereign AI Stack, which gives them policy-bound decision graphs, immutable audit trails, and a mandatory human approval checkpoint. Two are accessible live today; two are in active pilot development.
- Working systems, running under real institutional constraints
- Data never leaves the institutional boundary
- Use cases from DGCA, SAI, Odisha WRD, and the Odisha Legislative Assembly
- Outputs carry mandatory citations and an audit trail
- Human approval is enforced at every decision gateway
Live Operational Systems
Access these systems now. Logic, compliance engines, and orchestration are fully functional. All data is synthetic.
AAOIP: Aviation Intelligence Platform
Autonomous aviation disruption recovery (AOG, weather, crew limits) within strict DGCA protocols. Guided by a Constraint Trace Graph to visually explain policy rejections.
Core Capabilities
- Agentic IROPS recovery, with Fleet, Crew, and Weather agents working the same disruption
- A Constraint Trace Graph shows visually why a policy rejected an option
- The DGCA compliance engine blocks WOCL and FDP violations before they are proposed
- Fleet simulator mapping 420 aircraft
- Specialised intelligence nodes coordinate over a shared message bus
- Comparative replay confirms the 85.5% cost reduction is reproducible
- Knowledge graph queries resolve in milliseconds across airports, aircraft, and rules
- Digital twin covers fleet grounding, FDTL revisions, and network expansion
Platform Modules
- Executive Dashboard: 420 aircraft and 1,900 flights (live KPIs)
- Live Ops & IROPS: 4 distinct disruption scenario types
- Crew Rostering: FDTL gauges and fatigue risk scoring
- Predictive Maintenance: Engine EGT/N1 degradation charts
- Network Map: 33 airports, weather overlays, and IROPS
- ROI Dashboard: ₹700 to 1,250 Cr/year savings projection
- Regulatory Library: 10 DGCA CARs and 100 structured rules
- Retail Intelligence: Dynamic bundling and pricing analysis
Synthetic data environment. Recommended: Chrome/Edge full-screen.
NAISP: National Athlete Intelligence & Selection Platform
Sovereign sports selection engine. Rankings run through a policy-bound graph and are cryptographically sealed. Human overrides require typed justification.
Core Capabilities
- The adjudication controller ranks on six deterministic factors
- A SHAP waterfall exposes the mathematical contribution of each factor
- A KNN grassroots classifier maps trial data onto elite proxy vectors
- Six parallel nodes execute before the ranking is sealed
- Every step writes a hashed, immutable entry to the execution ledger
- An officer overriding the ranking has to record a rationale
- Anonymised mode conceals names and UAIs to prevent bias
- ACWR workload monitoring profiles predictive injury risk
Platform Modules
- Grassroots Talent Discovery: KNN classifier and one-click nomination
- Deterministic Adjudication: TOPSIS ranking and SHAP XAI
- Athlete 360° Explorer: Biomechanical radar and workload charts
- XAI & Governance: SHAP analysis and Execution Ledger
- Intelligence Chat: Natural language queries routed to TOPSIS
- Biomechanics Viewer: SVG analysis with historical diffs
- Sports Knowledge Graph: 15 athletes across 8 training centres
- Bulk Athlete Import: CSV validation and red-cell errors
Synthetic data environment. Default login: Sports Scientist / Admin.
Active Pilot Programs
Active pilot development with government clients. Briefings available to qualified stakeholders.
Integrated AI Water Intelligence Platform
Client: Water Resources Department, Government of Odisha
Primary Focus: Hirakud Dam & Mahanadi River System
An AI-assisted decision support system for dam release planning during flood cycles. Advisory-only: Models calibrate mathematics, not gate control.
TECHNICAL CAPABILITIES
- Multi-variate transformers produce a P10/P50/P90 inflow forecast
- A deterministic mass-balance model projects reservoir level independently
- Three scenarios simulated, including the recommended release
- Downstream impact is translated through a precise DEM
- Flood warning issued 12 to 24 hours ahead of IMD and CWC notice
- A weighted optimiser balances downstream risk against storage safety
- Every recommendation requires an officer login before it stands
- Advisory only. The system does not actuate gates
Status: Pilot development in progress. AI Inflow Forecast (LSTM/TFT) pre-trained on historical Hirakud data. Scenario simulator and downstream impact model in build. Demo delivery aligned with Odisha WRD engagement timeline.
Vidhan-Buddhi: Sovereign Legislative Intelligence
Client: Odisha Legislative Assembly (OLA)
Primary Case: Mahanadi Water Dispute (2016–2025)
Converts unstructured legislative archives into a verifiable intelligence layer. Runs entirely air-gapped on local models. No data egresses the Assembly.
TECHNICAL CAPABILITIES
- The Shoonya OCR factory handles preprocessing and feeds human verification
- Runs air-gapped on sovereign models, so nothing leaves the building
- Retrieval is evidence-first. An answer without a citation is not returned
- An agentic pipeline covers RAG research, data synthesis, and translation
- The Mahanadi water dispute demo correlates rhetoric from 2016 to 2025
- Semantic retrieval across decades of press cuttings and scanned PDFs
- An evidence board shows era-tagged documents with direct citations
- Runs entirely on a government laptop
Status: Shoonya OCR ingestion pipeline built. ChromaDB knowledge base seeded with Mahanadi Water Dispute dataset (2016–2025). Agentic reasoning core and Evidence Board UI in active development.
Built on the Same Sovereign Foundation
AAOIP, NAISP, Water Intelligence, and Vidhan-Buddhi are domain applications of Ooumph's Unified Sovereign Interface (USI). They share the identical policy-bound execution fabric, cryptographic audit architecture, and human-approval gateway model.
This secures procurement validity: Evaluating NAISP simultaneously evaluates the infrastructure supporting legislative intelligence, water management, and aviation operations. The platform investment scales laterally.
OSIE™: Ooumph Secure Inference Engine
Jurisdiction-pinned inference router. All payloads stay within sovereign boundaries.
OCRM: Ooumph Core Reasoning Model
Proprietary deterministic reasoning model. Replaces generic LLM dependencies.
Execution Envelopes
Cryptographically sealed decision records. QAI-compliant, RTI-defensible.
Policy-Bound Execution Graphs
Deterministic, reproducible DAGs. Same input → same output, every time.
Evaluate the Sovereign Architecture
Access the live systems immediately. For a structured technical briefing or a pilot scoping discussion, engage the Ooumph team directly.
Self-Directed Platform Evaluation
Access AAOIP and NAISP using the credentials above. Both systems include demo data and built-in scenario guides. No Ooumph staff required.
Guided Technical Briefing
A 45-minute structured walkthrough for technical teams, procurement officers, and senior administrators. Includes architecture Q&A and a pilot scoping discussion.
Schedule BriefingUSI Architecture Review
Review the full technical specification for the Unified Sovereign Interface — the infrastructure layer underlying all four platforms. Relevant for CTO and security architecture evaluations.
Review ArchitectureTechnical enquiries: demos@ooumph.com · info@ooumph.com
Offices: Lucknow · Delhi · Bhubaneswar · Bhopal