Industry · Aerospace · Commercial
The data, records, and maintenance-intelligence layer for commercial aviation.
We build commercial-grade business and AI software for the aviation and aftermarket ecosystem — maintenance-records intelligence, predictive-maintenance analytics, fleet- and asset-data apps, and the MRO-adjacent workflow tools off-the-shelf systems leave uncovered.
Commercial business software only — no classified, ITAR/EAR, flight-critical avionics, or safety-of-flight certified work.
From records to answers
The problem
Why so much aviation data still sits in paper, PDFs, and silos.
The aerospace ecosystem runs on records, and most were never built to be queried. A single aircraft carries a back-to-birth paper trail — maintenance logs, airworthiness directives, component genealogy — much of it scanned, hand-written, or locked in formats no system reads.
Fleet, sensor, and MRO data lives in separate silos. The result is the most expensive failure mode in the business: the information needed to keep an aircraft flying, prove compliance, or close a transaction exists somewhere — but finding and trusting it takes days, not minutes.
Closing it isn't a new ERP or a rip-and-replace — it's the focused software that turns documents and signals into answers.
projected CAGR for global commercial aftermarket MRO demand, 2026–2035 — operators flying existing fleets longer against deep production backlogs.
projected US A&D AI spending by 2029 — about 3.5× its 2025 level. The spend is real; the question is whether it reaches production.
Deloitte, Nov 2025 ↗
What we build
Where commercial aerospace software earns its keep — and what each use case delivers.
High-leverage applications that sit on top of the systems and records a commercial aviation operation already has. Every example is illustrative of the technology — not a Silicon Prime client result.
Maintenance-records intelligence (document AI)
Reads scanned logbooks, work orders, and airworthiness records, then structures them so an asset's status, gaps, and compliance can be queried in plain language.
Benefit — critical records surface in minutes, not days, gaps caught before they cost you.
Example: a lessor assessing an aircraft for redelivery gets a structured back-to-birth picture and the missing-document list from a stack of PDFs in minutes — not a week reconciling paper.
Predictive-maintenance analytics
Learns a component's normal signature from sensor and historical data and flags the deviation that precedes failure — turning a reactive removal into a planned one.
Benefit — fewer unscheduled removals and grounded aircraft, better-planned MRO visits.
Example: a part trending out-of-limit is flagged before a flight, so it's swapped on a planned overnight instead of triggering an aircraft-on-ground event next morning.
Fleet & asset data platforms
Unifies utilization, reliability, configuration, and cost data across a fleet into one trusted view — decisions run off live data, not month-end spreadsheets.
Benefit — faster, better-grounded reliability and planning decisions.
Example: a reliability engineer sees a component's removal rate climbing across the fleet in real time and triggers a review before it becomes a recurring AOG driver.
MRO-adjacent workflow applications
The targeted app off-the-shelf platforms don't cover — a turn-time tracker, parts-and-tooling visibility, a hangar-floor data-capture app — integrated with your M&E or ERP.
Benefit — purpose-built software for the workflow you actually run, no multi-year migration.
Example: a heavy-check bottleneck gets a focused app that surfaces the stuck task and its blocking part live, so the shift lead reroutes work instead of finding the slip at day's end.
Compliance, traceability & audit support
Stitches records, parts, and inspection data into a provable, queryable genealogy so an audit or transaction closes against trusted data, not a manual document hunt.
Benefit — faster audits and transactions, far lower records risk.
Example: an airworthiness review pulls a complete, traceable history for a life-limited part on demand instead of pausing while someone searches the archive — a gap that can cost millions in a transition.
"We build the commercial enterprise layer — software that sits alongside your operation, never inside the aircraft."
See the full scope →The measured impact
What this software does to the work.
Independent, third-party findings on the commercial aerospace and aftermarket sector — cited as industry evidence, not Silicon Prime client results. We have no aerospace engagement; this is the published industry record.
Share engine MRO is rising toward
of total MRO demand, as global aftermarket demand grows ~3.2% CAGR 2026–2035 — the size of the prize a records-and-analytics layer captures.
Deloitte, Nov 2025 ↗
Projected US A&D AI spending by 2029
about 3.5× its 2025 level, with ~36% of industrial-products tasks able to benefit from agentic AI. The spend is real; the question is production.
Deloitte, Nov 2025 ↗
Records retrieval, GE Aerospace
with Microsoft and Accenture, a generative-AI tool surfaces critical asset records "in minutes versus days and weeks" — a named, public example the approach works.
GE Aerospace, Nov 2024 ↗
Commercial-grade only — and we'll tell you when we're not the firm.
No security clearances, no ITAR or EAR registration, no cleared personnel or facilities, no classified-program experience, no flight-critical or DO-178C avionics. If your work requires clearances, ITAR/EAR controls, or CMMC-level compliance, we are not the right firm — and we'll say so up front rather than take the engagement.
The scope
What commercial aerospace software development covers.
The commercial business-software and intelligence layer. To be explicit: no flight-critical or airborne avionics, no DO-178C certified software, no classified or ITAR/EAR-controlled defense work.
Maintenance-records & document intelligence
Document-AI pipelines that turn scanned logbooks, work orders, and airworthiness records into structured, queryable data — with the validation that makes the output trustworthy enough to act on.
Predictive-maintenance models
ML models that learn a component's normal behavior and flag pre-failure drift, validated against your historical removal and failure data so alerts are trustworthy — not a false-alarm generator the line ignores.
Fleet & asset data platforms and analytics
Real-time and historical analytics over utilization, reliability, configuration, and cost data — unified by line, tail, and component — so planning runs off trusted live data.
MRO-adjacent & M&E/ERP-integration apps
The targeted apps a maintenance operation needs that off-the-shelf systems don't cover, integrated with the M&E or ERP you already run — without a multi-year migration.
Compliance, traceability & audit support
Stitches records, parts, and inspection data into a provable, queryable genealogy — so an airworthiness audit or aircraft transaction closes against trusted data, not a manual document hunt.
Data integration & modernization
Connecting the M&E, ERP, sensor, and records systems you run into one trusted record, and modernizing the legacy commercial tools too brittle to build on — without ripping out what works.
What you get — all assigned to you under full work-for-hire IP transfer
How it runs
One accountable lead, fixed scope, no handoffs.
Tuned for a records-heavy, compliance-sensitive commercial operation. Most engagements reach production in 4–8 weeks, full IP assignment signed at kickoff.
Discover
Scope the use case and the loss it targets — records-retrieval time, unscheduled removals, audit turnaround — and confirm the data supports it, with the honest "not a fit" call included.
Output: a ranked plan & the metric we'll be judged on
Connect
Pull records, M&E, ERP, and sensor data into a usable store through governed, read-only pipelines — commercial data only, fully documented.
Output: a trusted data foundation
Build
Develop the app and, where it applies, train and validate the model against your historical data — measuring accuracy on your own records before anything goes live.
Output: a working system tested on your real records
Deploy & enable
Pilot on one records type, fleet, or hangar, prove the metric moves, then scale — your team trained to operate, retrain, and extend it.
Output: a production system & a team that owns it
The track record
No aviation client — but the records and reliability engineering the work demands.
We'll be straight: we have no aerospace or defense clients, and we won't dress adjacent work up as aviation. What transfers is the engineering rigor and asset-data familiarity records intelligence and predictive maintenance demand.
Our named cases are in restaurants (BJ's, a 200+ location operation held at zero critical defects for four years) and a heavy-equipment marketplace (YardClub, acquired by Caterpillar — deep machine-and-asset data familiarity). For a first aviation engagement we scope a contained pilot on one records type or one fleet to prove the value first.
The records-intelligence pattern is proven — by others, publicly. GE Aerospace, with Microsoft and Accenture, shipped a generative-AI tool that surfaces critical asset records "in minutes versus days and weeks." We cite it as evidence the approach works, not as our project.
Silicon Prime is a Stanford-rooted Responsible AI lab, founded in 2011, run by founder Kelvin Tran. If you need a vendor with a deep aviation track record, we'll tell you that plainly.
YardClub
A heavy-equipment marketplace built end to end — listings, asset records, payments, transaction infrastructure. $120M+ processed; acquired by Caterpillar in 2017. Deep machine-and-asset data familiarity, adjacent in rigor.
BJ's Restaurants
A 200+ location operation held at twice-a-week releases with zero critical defects across four years — the production-reliability engineering a records or analytics system the operation depends on has to clear.
Why build it with us.
Honestly scoped — commercial-grade only. No clearances, no ITAR/EAR, no avionics, and we say so up front. That boundary means a faster, lower-risk engagement and zero overpromising on work we can't do.
Document AI, built to be trusted. We build extraction with validation and measure accuracy against your own records before it goes live — the difference between a records tool the team relies on and one it learns to second-guess.
Asset-data depth from an adjacent build. YardClub gave us deep machine-and-asset data familiarity, and BJ's the production-reliability bar — the engineering a records and analytics layer the operation depends on has to clear.
Founder-led, built to transfer. One accountable lead; the code, models, and pipelines are assigned to you, your team trained to run and retrain them when we step back.
Where this connects
A records-and-analytics build rarely stands alone.
It rests on the same engineering we bring to neighboring work.
Data & analytics engineering
The trusted-data foundation records intelligence and fleet analytics run on — so the records are trusted before anyone relies on them.
Data engineering →Machine learning development
The predictive-maintenance and document-AI models — validated against your historical records before they go live.
ML development →Manufacturing software
The same predictive-maintenance and asset-intelligence engineering, applied to the production floor.
Manufacturing software →Questions buyers ask before they build.
Do you have security clearances, ITAR registration, or defense-program experience?+
Do you build avionics or flight-critical software?+
Do you have aerospace clients we can reference?+
What can document intelligence realistically do for maintenance records?+
How do you handle our data and security?+
Who owns the software and models when you're done?+
How fast can we see something working, and what does it cost?+
Thirty minutes · No pitch deck
Ready to turn records and signals into answers in minutes?
Bring the commercial-aviation problem — a records backlog, a predictive-maintenance goal, a fleet-data gap — and we'll tell you honestly whether your data supports it, what it takes to build, and where the boundary of our work is.