The platform
Each application does one part of the work — and hands its evidence to the next. Use them together, or one at a time.
Platform overviewSee how the loop runs
DjiniousEngineeringOrchestration
DjiniousLabModelling & simulation
DjiniousWorkshopSystem integration
DjiniousSafeCertifiable code
DjiniousWorld3D replicas
DjiniousMapAgent GIS
DjiniousCCOperations & SCADA
DjiniousDataKnowledge base
DjiniousWorkflowAgent automation9 appsOne engineering platform
A team of specialised AI engineers carries a unique need from requirements and simulation through integration, proof and manufacturing preparation — and keeps it running once it ships.
How it works
State the outcome once. Six stages carry it to a running system — each done by the applications that own it, each leaving an artifact the next stage can trust.
Stage 1 · Assign
The assignment lands on DjiniousEngineering, which decomposes it into requirements on a live System Ledger. DjiniousData brings the governed knowledge the need depends on — documents, fleets, sites — as evidence, not hearsay.
Hands onA System Ledger: every requirement a typed, traceable item.
DjiniousEngineering
The applications
Grouped by the part of the work they do. Every one is a product you can adopt on its own; together they share one ledger and one twin.
Receives the assignment and drives the project across every application.
Model the system, integrate it with physics, and prove the code it runs.
DjiniousLabModelling & simulationMulti-domain system models, digital replicas and a mathematical toolbox, driven by AI.
DjiniousWorkshopSystem integrationComponents wired into a complete system and closed through GPU physics in NVIDIA Isaac Sim.
DjiniousSafeCertifiable codeLean 4 specifications and kernel-checked proofs turned into panic-free embedded Rust, up to SIL 4.
The world around the system, as agents and engineers can read it.
Supervise, control and improve the system once it is deployed.
The data and the automation every stage can call on.
Together or alone
Every application is a world of its own and can be used independently. Connect them and the handoffs start carrying their evidence.
Assign the project once and the applications work as one engineering team. Each handoff carries its evidence, so what the Lab simulated is what the Workshop integrates, what Safe proves and what CC supervises.
Every application is a world of its own. Start with the one your team needs today — a SCADA, a modelling studio, a geospatial control plane, an automation engine — and connect the others when the project calls for them.
AI engineers
The work happens on a live System Ledger: every requirement, model, verification and gate as typed, traceable items across the ISO 15288 lifecycle — so you can see what each agent did, and why.
Each engineering discipline works through its own governed tools — models, physics, proofs, SCADA — not one general assistant guessing across all of them.
Review gates sit between lifecycle stages. Agents propose, show their tool trace and wait; people approve what moves forward.
Every handoff carries simulation results, decisions and traceability. A claim without its evidence does not reach the next stage.
AI accelerates the work but is never the only path: models, proofs and procedures run, replay and verify without it.
DjiniousEngineeringDjiniousEngineering
Use cases
62 worked cases — from subsea autonomy and grid-scale storage to process plants, robot cells and governed geospatial data.
Subsea autonomyMarlin-XR Seabed Survey AUVAn autonomous underwater vehicle surveying the export-cable corridor of the Dogger Bank offshore wind farm. The bundled demo ledger: forty items seeded across all eleven lifecycle stages, from the mission brief to the deployment procedure.DjiniousEngineering
Uncrewed aircraftKestrel-1 Survey UAVA fixed-wing survey UAV, seeded as a worked example: eight requirements, six components, four suppliers and four verifications, wired into a traceability graph, with a real ELANG system_model and an inline Technical Data Package.DjiniousEngineering
RF & radar sensingEmbedded Radar Sensing ModuleAn embedded radar sensing module — the system class the RF/radar recipe covers: a mixed-signal board where spectrum, EMC, environmental and fabrication standards constrain the design as hard as the sensing requirement does.DjiniousEngineeringEnterprise-ready
Built for teams whose systems are safety-critical, regulated or simply too expensive to get wrong.
Isolation lives in the data layer — row-level security and per-verb permissions — not in application code that can forget it.
DjiniousMap · DjiniousDataKernel-checked proofs, diverse code generation and machine-checked traceability bundled with each build, aimed at IEC 61508 SIL 4.
DjiniousSafeRun state lives in the database, so a run survives any restart; every node execution is recorded and every page traces back to its run.
DjiniousWorkflowREST and MCP for agents and systems, FMI for models, standard field protocols for plants — no lock-in at any boundary.
REST · MCP · FMIEngineering journal
Lessons from building and verifying an AI-defined, safety-critical ERTMS/ETCS system.
A candid engineering account of directing AI agents to build a complete railway signalling system at extraordinary speed—and the verification lessons that followed.
AIERTMSSafetyRead on ertms.ignitial.ioHow AI can operate as a governed co-engineer across requirements, architecture, implementation, testing, documentation and safety analysis.
AISIL4RustRead on ertms.ignitial.ioA practical look at closed-loop testing where the EVC, RBC and train-dynamics simulator interact against real system-level scenarios.
SimDeskTestingDemoRead on ertms.ignitial.io
Djinious
