Built for real-time intelligence at institutional scale.
MIOS is engineered to handle the data volumes, latency requirements, and operational availability demands of governments and crisis command centers. This is the infrastructure that makes intelligence at speed possible.
Three-layer intelligence pipeline.
Signal Ingestion Layer
High-throughput, fault-tolerant ingestion pipeline designed to collect narrative signals from hundreds of concurrent sources with sub-second latency from publish to processing queue.
- Distributed streaming architecture for parallel ingestion
- Adaptive crawl scheduling based on source activity patterns
- Deduplication and noise filtering at ingestion boundary
- Multi-language content normalization pipeline
- Source reliability scoring and signal weighting
- Horizontal scaling with no single point of failure
OSIRIS AI Processing Layer
Multi-model AI reasoning pipeline that classifies, clusters, attributes, and forecasts based on the signal stream. Designed for inference speed without sacrificing classification accuracy.
- Parallel inference across specialized model ensemble
- Real-time narrative clustering and thread tracking
- Graph-based influence network construction
- Escalation trajectory forecasting models
- Confidence calibration and uncertainty quantification
- GPU-accelerated inference with dynamic batching
Intelligence Delivery Layer
Low-latency output layer that translates AI analysis into structured intelligence products — briefings, alerts, API responses, and dashboard state updates — and delivers them to command infrastructure.
- Sub-100ms dashboard state update latency
- Webhook and API push for real-time alert delivery
- Structured briefing generation with export formatting
- Priority alert routing with escalation logic
- Command-ready output formatting for decision-makers
- Audit-logged delivery confirmation for all critical alerts
Engineering targets we build to.
| Metric | Target | Notes |
|---|---|---|
| Signal ingest to classification | < 90 seconds | End-to-end latency, standard sources |
| Dashboard update latency | < 100ms | State push to connected clients |
| Alert delivery latency | < 30 seconds | From classification to operator alert |
| Platform availability | 99.9% uptime | Measured monthly, per SLA |
| Concurrent source monitoring | 500+ sources | Configurable per deployment scope |
| Languages supported | 12+ languages | Native processing, not translation layer |
| Data encryption | AES-256 / TLS 1.3 | At rest and in transit |
How we engineer for operational reliability.
No Single Point of Failure
Every critical system component — ingestion, processing, storage, delivery — runs with redundant instances. A single node failure produces zero operator-visible disruption.
Graceful Degradation
Under extreme load, MIOS prioritizes high-severity intelligence delivery over lower-priority functions. Critical alerts are always delivered first, even when the system is under stress.
Stateless Processing
Intelligence processing pipelines are stateless wherever possible. This enables horizontal scaling under load spikes — election days, breaking crises — without configuration changes.
Observable by Design
Full distributed tracing, structured logging, and real-time metrics across all system components. Operators can always see exactly what the system is doing and why it produced a given output.
Sovereign Deployability
The full MIOS stack — including AI models and all processing — is containerized and deployable on sovereign or air-gapped infrastructure. No cloud dependency is required for core functions.
Continuous Delivery
Platform updates are deployed continuously via automated pipelines with staged rollouts. Clients see improvements without scheduled maintenance windows or disruptive upgrade cycles.
Build the intelligence infrastructure of tomorrow.
We're hiring engineers who want to work at the intersection of AI, distributed systems, and institutional intelligence. If you want to build infrastructure that operates where stakes are highest, we want to talk.