Built and instrumented in production — every product below links to measured results, not projected ones.
The platform
Our architecture connects operational systems, specialized agents, enterprise intelligence services, and governed outcomes. Instead of deploying isolated chatbots, we build an AI operating layer that can plan work, call approved tools, collaborate across roles, and produce auditable business actions.
Domain-trained agents, each combining ML forecasting models with LLM-driven reasoning over a shared data-ingestion and orchestration layer.
Forecasts demand, flags anomalies, and drafts reorders across procurement and inventory data — Prophet, XGBoost, and LSTM models behind a single conversational interface. ERP-integrated.
Reinforcement-learning route optimization fed by live GPS telemetry and vehicle/environmental sensors, built to communicate across institutional boundaries using our SovNet agent-interoperability protocol.
Continuously monitors news, pricing, and sentiment signals; ranks relevance, predicts near-term trend direction, and scores opportunity/risk — with adjustable recency and depth.
Agent deep dive
The forecasting agent turns fragmented commercial and inventory inputs into a repeatable decision workflow. It validates incoming data, generates SKU-level forecasts, evaluates stock risk, recommends inventory actions, and summarizes the rationale for business teams.
Agent deep dive
The Opportunity Intelligence Agent replaces periodic, disconnected research with an always-on intelligence workflow. It gathers market and competitor signals, ranks relevance, identifies emerging themes, supports market sizing, and prepares decision-ready insights for strategy and growth teams.
Same underlying token-optimization stack — prompt/prefix caching, adaptive retrieval, semantic caching, KV-cache quantization — applied per domain.
Contract review and M&A due-diligence copilot — query large contracts and data rooms directly instead of manual clause-by-clause review.
| Tokens per clause-query | 12,000 → 2,100 |
|---|---|
| Analyst turnaround | 3.5 hrs → 1.2 hrs |
| Cache hit rate | ~45% |
Ambient clinical documentation — converts doctor-patient conversations into structured notes automatically, scaling patient volume without proportional staffing.
| Cost per note | $0.18 → $0.05 |
|---|---|
| Concurrent sessions/GPU | 12 → 34 |
| Clinics on same budget | 2 → 40 |
AI pair-programmer for multi-million-line monorepos — navigation, refactoring, and testing without re-sending full repo context on every call.
| Cache hit rate | 0% → 81% |
|---|---|
| Tokens per refactor task | 54,000 → 16,000 |
| Concurrent sessions | ~5× |
Equity research and earnings-call analysis agent — extracts insights from filings and transcripts to expand coverage without adding headcount during earnings season.
| Inference calls, earnings week | −58% |
|---|---|
| Peak-week infra cost | $61,000 → $24,000 |
| Ticker coverage | ~3× |
Copilot architecture
A shared enterprise AI foundation supports legal, healthcare, engineering, finance, and custom departmental copilots. Each experience is tuned to its domain while using consistent access controls, integration standards, observability, and governance.
Product deep dive · LexGuard AI
LexGuard AI is designed around the complete legal-review journey—not just document chat. It organizes source material, extracts clauses, compares revisions, identifies risk, supports due diligence, and maintains a traceable document workflow for legal teams.
Product deep dive · MediScribe AI
MediScribe AI supports the documentation journey from consultation-room audio to structured clinical records. The system recognizes domain vocabulary and speakers, organizes relevant clinical context, prepares structured notes, and connects the result to approved healthcare workflows and EHR systems.
Product deep dive · CodePilot Enterprise
CodePilot Enterprise is designed to understand large, interconnected codebases and support engineering work beyond autocomplete. It brings repository context, code reasoning, testing, delivery automation, deployment infrastructure, security controls, and team collaboration into one governed developer workflow.
Product deep dive · FinSight Analyst
FinSight Analyst brings market monitoring, earnings analysis, financial-statement review, semantic research, and predictive analytics into one governed research environment. It is designed to help analysts expand coverage and move from source material to an evidence-backed investment view faster.
Scans surveillance footage to identify and extract clips of persons of interest using facial embeddings and multi-camera correlation. Real-time stream analysis and historical archive search, deployed SaaS or on-premise. GDPR-ready with optional face blurring.
| Transcription accuracy | 80% → 90–92% |
|---|---|
| Manual correction time | −50% |
Vision and speech platform
Our multimodal platform combines visual perception and speech intelligence with edge processing, cloud analytics, and enterprise security. The same governed foundation can support real-time monitoring, historical search, transcription, structured extraction, and downstream workflow automation.
Product deep dive · CCTV Analyzer
CCTV Analyzer is designed to turn distributed surveillance feeds into structured, reviewable events. It supports detection and correlation across cameras, creates event timelines, enables forensic search, and delivers operational insight through monitoring and analytics interfaces.
A four-tier network architecture (Public, Authenticated, Institutional, Classified/air-gapped) with a common seven-layer protocol stack, enabling interoperable communication between sovereign AI agents across institutional and security-classification boundaries. Status: provisional filing preparation is in progress — not yet filed or granted.
These four cards need real content before publishing — no verified scope, tech stack, or filing status exists yet for any of them.
SovNet · Concept architecture
This concept visual represents the type of controlled agent environment SovNet is intended to support: distributed AI services, protected enterprise infrastructure, policy enforcement, identity-aware communication, monitoring, and traceable outputs across organizational boundaries.
