AI inside the operator's perimeter. Evidence-ready by design.
Mission-critical AI inside your operations. Safety data stays inside.
This page covers commercial aviation — passenger and cargo operators, MRO organisations, and commercial flight training. Defense, military, and classified contexts sit outside scope.
A layered envelope no off-the-shelf AI was built to fit.
Your operation sits inside a layered envelope. Safety frameworks govern dispatch, maintenance, and crew. Regulator scrutiny on AI use is rising in parallel. Passenger-data law sits alongside. The off-the-shelf AI platform was not built for this stack.
deeplinq plugs into the systems that already run your operation — ARMS, AMOS, Sabre or Amadeus, Lufthansa Systems Lido, EFB content management, FRMS — and reads operations, MRO, customer, and crew state as one queryable surface. Plain-language questions return sourced answers with a citation trail. In on-premise and air-gapped deployments, every prompt, retrieval, and agent action is archived behind your firewall, not behind ours.
GDPR, PDPL, Loi 09-08, nLPD, or your regional equivalent frames passenger-data handling. ICAO, EASA, FAA, and your national CAA frame safety.
Sourced context for your dispatcher, not a replacement for the decision.
It is 03:14. A storm cell shifts. Three diversion candidates compete on fuel, slot, and crew duty. Your dispatcher pulls ARMS on one screen, weather on another, NOTAMs on a third, the CRS message on a fourth. The clock keeps moving.
The platform queries one contextual layer that aligns ARMS, dispatch consoles, weather, CRS messaging, and NOTAM feeds. Before : the dispatcher pulls four screens in sequence — ARMS, weather, NOTAMs, CRS — while the clock keeps moving. After : agents surface a sourced picture inside the existing console, with diversion options weighed against fuel, slot, and crew duty and each line cited back to the originating record.
Aligned with EASA Part-OPS, ICAO Annexes 1, 6 and 8, and EU 376/2014. Operational authority remains with your Pilot in Command and dispatcher under licence. deeplinq prepares the context. Your team makes the call.
Maintenance documentation, cited back to the manual page that proves it.
Your AD, SB, and tail number rarely meet on the same desk. AMOS holds the history. Manufacturer portals hold technical publications. Paper records hold the rest. A pre-task lookup costs hours your hangar does not have.
The platform cross-references each tail number to AD and SB applicability across AMOS, manufacturer technical publications, AD and SB feeds, parts inventory, and vendor portals. Before : the certifying engineer chases AD, SB, and tail history across AMOS, manufacturer portals, and paper records — hours per pre-task lookup. After : staff ask in plain language ('is this tail compliant with AD 2024-18-09 after the last C-check?') and receive a sourced answer with the AMOS work-order, manual page, and SB reference attached.
Aligned with EASA Part 145, Part M, Part 21, FAA Part 145, and ISO 9001. Airworthiness certification stays with your Part 145 organisation — what changes is the time to assemble the supporting record.
Multilingual passenger context, drafted from one view of the file.
What does your L1 agent see when a passenger calls during an IRROPS event in their third language? PNR on one tab, CRM on another, loyalty in a third, the recorded-call archive in none of them. By the time the picture is whole, the call is over.
The platform surfaces a coherent passenger view across PNR, CRM, loyalty, recorded-call archives, and complaint history — in the language the passenger is calling in. Before : the L1 agent toggles four tabs while the IRROPS call ends. After : your L1 and L2 staff receive sourced context during IRROPS or routine calls, and a subject-access-request draft is produced from the unified view — review and release left to your agent.
Subject-access and rectification rights apply per your regions of operation, framed by your data-protection regime. Auto-rebooking and auto-compensation stay with your agent — the system drafts, your team approves.
Roster, qualifications, and EFB queries answered against a single state.
Three rostering systems. Five qualification certificates per crew member. Twelve EFB document revisions a quarter. Your crew controller stitches that by hand — the gap between the duty record and the FRMS reading is where errors live.
The platform indexes rostering, qualifications, training records, EFB content management, and FRMS into one queryable state. Before: roster questions, currency checks, and EFB lookups travel through three or four systems and a spreadsheet. After: your controller asks once and receives an answer cited back to the source training record, roster entry, or document version.
Aligned with EASA Part-FCL, Part-MED, ICAO Annex 1, and fatigue management frameworks (CASA, FAA AC 120-103A, EASA FTL). Crew availability calls stay with your controller. The system reduces the search. Your controller still signs.
What your regulator, your auditor, and your Just Culture review actually receive.
When EASA writes, when your auditor opens a file, when a Just Culture review reconstructs an event — the question is the same. Show the trail. deeplinq treats the evidence layer as a first-class platform concern: every prompt, retrieval, model call, and agent action is archived with full context, source attribution, and an RBAC trace tied to the user who issued it.
Model-version pinning is the structural backbone. The model that produced an output during one audit cycle reconstructs the reasoning during the next. Reporting templates, retention parameters, and lawful-basis annotations stay versioned alongside the interactions they cover. Exports run in the formats your safety, compliance, and DPO functions already submit.
Safety compliance stays with your operator, your safety management system, and your certifying staff under licensure — that authority belongs there. What deeplinq delivers is the evidence trail those functions expect to see.
Residency shaped by the data, not by a single answer.
Aviation data does not share one residency profile. Passenger records sit under your data-protection regime. Operational data is framed by safety reporting. Crew records sit under labour and licensing rules. Manufacturer documentation falls under contractual handling. Your topology has to fit each.
Four deployment modes meet that reality — on-premise inside your data centre; customer-tenanted private cloud (VPC) on AWS, Azure, or Google Cloud; a regional sovereign cloud aligned with your hosting requirements; and a deeplinq-managed cloud where your compliance posture allows it. The topology bends to your data, not the reverse.
Model choice sits behind an interface your operator controls. Cloud APIs for non-sensitive workloads — OpenAI, Anthropic, Mistral, Google. Open-weights for on-premise or air-gapped — Llama, Qwen, Mistral open, Gemma, Falcon. The full posture is detailed on /banking-regulated.
Start a conversation. Not a sales process.
A working session with our team — on your operational envelope, your safety reporting frameworks, your deployment constraints, and the workflow where the evidence posture matters most for your operator. Bring your audit cadence. We'll bring the evidence model.