Every sortie generates evidence.Mantis reads it across the fleet not just asset by asset.Then turns it into readiness for the warfighter and the next iteration for the OEM.Any platform. Any domain.
Calibrating the right asset to a mission means weighing weather, terrain, operator performance, and mission profile all at once. Difficult for a single asset. Nearly impossible across a fleet. Mantis does it continuously, fleet-wide.
Hover a segment for provenance · hover FMC for the readiness projection
Platforms, figures, and insights shown are synthetic: illustrative sample data for demonstration only and not derived from any real fleet.
Close the loop across any OEM. Any domain.
Per-flight & fleet-wide
Scored per component
Anticipates demand & sourcing risk
Agent-drafted · full audit trail
Sustainment closes one loop. Feeding what happens downrange back to the people who build the aircraft closes the other.
Every signal off the vehicle flows through the same loop, so a shift in how a platform is flown becomes a change in what wears, what ships, and what gets staged before it's needed. Mantis closes that loop automatically, turning raw telemetry into fleet readiness. The same evidence closes a second loop the flightline never had: how parts actually perform downrange, routed back to the OEMs who build them. In days, not quarters.
Five capabilities that turn a mixed-OEM fleet into a single, decision-ready system.
One normalized fleet view across every OEM and platform: air, ground, and sea. The telemetry pipeline reconciles vendor-specific log formats into a common schema, so commanders, maintainers, and analysts all see the same picture.
How parts truly perform downrange flows back to the OEMs who build them, a signal that historically never made it off the flightline. The evidence behind it is captured per component: every flight is auto-evaluated against manufacturer envelopes (altitude, speed, temperature, voltage), each component carries a remaining-useful-life score, and fleet-wide pattern recognition aggregates motor, GPS, thermal, and battery signals to surface systemic issues before they ground assets. That same record is what shortens the distance between a failure in the field and a design change on the line.
Agents draft work orders, BOM suggestions, and root-cause analyses. Operators approve. Every state change is audited.
Demand signals from work orders flow through BOM reservations, multi-supplier sourcing, and an animated material-flow view from supplier → inventory → fleet → retired. AI-assisted BOM build and component sourcing close the loop on procurement.
A 12-week asset readiness twin projects fully- and partially-mission-capable status by team. MantisML tracks model confidence as fleet composition changes. When drift exceeds a threshold, operators review the signal trail and propose retraining.
From planning the mission to sustaining the fleet.
Plan AOIs, drop zones, and corridors on a live drawing surface. Place sensors, effectors, and threats with range-ring visualization and per-placement paths.
Categorized diagnostic patterns across motor, GPS, thermal, and battery signals, aggregated fleet-wide to surface systemic issues before they ground assets.
Per-flight reconciliation of jamming and interference against a daily hotspot map, plus GPS dead-zone clusters linked back to the originating flight logs.
Every flight auto-evaluated against manufacturer envelopes, with battery health, event annotations, and confidence-scored contributing factors.
A 12-week asset readiness twin projecting fully- and partially-mission-capable status by team, so commanders can see readiness before it slips.
Tokenized, no-install field-tech links capture photo, video, and audio across motors, battery, airframe, and payloads, reconciled to flight logs.
Mantis thesis sizzle reel
Every decision. Auditable.
Capability is table stakes. In regulated and contested environments, what matters is whether you can explain and defend every decision.
Contributing factors are drawn from a fixed, reviewable vocabulary, not free-form model output.
Every ranked factor and agent suggestion carries a confidence score you can weigh.
Agents draft; operators decide. No autonomous state changes. Graduated autonomy by design.
Every transition, comment, and approval is append-only and attributable.
One platform. Three operating realities.
Maximize uptime across mixed-OEM commercial fleets with per-component RUL, automated maintenance, and closed-loop parts supply.
We ingest and standardize telemetry from every OEM in your fleet, then close both loops: a unified real-time view that drives agent-drafted maintenance and the parts to keep it flying, and the field evidence that reaches the people who build it.
