Trust before autonomy
IRIS compliance, OEM security, grounding, audit, human-in-the-loop and graduated control. The level is a dial the plant turns, and the weld procedure is the last thing it changes.
About
Rail vehicles are judged at the wheel-rail contact. The plant should not run on memory.
Railira exists to give every rolling-stock plant a system that runs carbody welding, bogie assembly, coating, fit-out, marriage and sequencing itself, standard-compliant, on takt, with less rework and line stoppage, and to capture the craft of a retiring workforce before it disappears. The vision is to become the autonomous operations layer for the world's rail rolling-stock manufacturing.
Mission
Make rail rolling-stock manufacturing autonomous, standard-compliant and on takt
So plants can meet the fleet-renewal and electrification launch cadence despite a shrinking skilled workforce.
VisionBecome the system of action for the world's rail rolling-stock manufacturing: every carbody welded, joined, coated, married and coupled, and every rail vehicle quality-assured on Railira.
Why
Why we are building this
The fact on the plant floor that started it.
The industry that builds the rail fleets the world moves in still runs on periodic audits, offline metrology and sampled inspection, while the skilled operators, body engineers and quality engineers who know how to weld, coat, marry and torque a rail vehicle to spec are retiring by the year. Fleet renewal, electrification and transit expansion say launch more, faster, in more variants. The workforce says it cannot.
Rolling-stock manufacturing is not one problem. It is a chain of tightly coupled ones. A weld parameter drifts, so a carbody distorts, so the geometry fails at fit, so the car is held or reworked, and the line rents for tens of thousands of dollars a minute while it waits. Point tools attack one link and miss the chain. Railira is built to run the whole chain as a single plant-edge system that senses, decides and acts, then learns from what happened.
Why now
- Fleet renewal, electrification and transit expansion compressing launch timelines and multiplying variants down the same line
- Reshoring of rolling-stock and battery-rail capacity standing up plants faster than skilled operators can be hired
- Line stoppage economics of tens of thousands of dollars a minute, and IRIS, TSI, AAR and APTA stakes on every car
- Robotic welding and coating, in-line metrology and vision, torque telemetry, edge inference and train-and-plant twins mature enough for the assembly line
Principles
How we build
The principles we work by.
Compounding data
Every supervised correction trains the system. The closed-loop chain from weld to geometry to coating to torque to acceptance is the asset.
Land narrow, expand
One process, one metric, one baseline agreed in writing. Then the plant. Then the network.
Cite everything
Every answer from the reasoning layer carries its source. Every action carries its evidence and its envelope.
Isolate tenants
Designs, control plans, program data, models and memory never cross a customer boundary. On-prem for those who need it.
Say what is planned
Figures are design targets until they are measured. Scenarios are labelled scenarios. Standards are cited, not claimed.
Focus
What kind of company this is
For anyone checking eligibility or category.
- An independent, pre-IPO startup building original physical-AI software for rail rolling-stock manufacturers
- A product company, not a consultancy, systems integrator, reseller, outsourced development shop or division of an automation supplier; services are limited to deployment, integration and assurance support for the platform
- Not a cloud provider and not associated with cryptocurrency
- Pre-launch and pre-revenue. Incorporation, headquarters and headcount are not published yet and nothing on this site should be read as claiming them. Leadership biographies are placeholders until verified
Run timeline · scenario
What we are actually building
Every Railira run is an ordered, inspectable sequence. This is run_9b4e27: Car 07 of a 4-car metro consist · shell line B · bogie shop · booth 2 · marriage station. Scenario completes in 10 steps with one approval gate. Shell geometry held inside tolerance after a twin-ranked weld sequence, one heat-input change approved by the shift weld engineer, two torque traces routed to rework before brake test, the livery cure window protected in the sequence, marriage interface inside tolerance, car released with full genealogy.
run_9b4e27
car 07 · 4-car metro consist
illustrative scenario
SUCCEEDED
-
01
ingest.order
SUCCEEDED
0.8 s
Plant Orchestrator · Pulled the work packages for car 07 from MES and PLM: aluminium extrusion shell, EN 15085 weld class per joint, control-plan geometry tolerances, bogie torque specifications, livery recipe and cure window, fit-out and marriage sequence. Locked the approved control-plan envelope for the shift.
-
02
takt.sequence
SUCCEEDED
41 s
Line-and-Logistics · Sequenced the shift against live readiness: booth 2 cure window, bogie B-14 readiness, brake-test slot at 13:40, AMR fleet state and kit inventory. The plan moves car 07 marriage behind car 06 to keep the cure window and the test slot.
-
03
twin.simulate
SUCCEEDED
58 s
Train Twin · Simulated 18 candidate weld sequences for the roof-to-sidewall joints on the as-built twin and ranked them on predicted distortion, door-aperture geometry and heat input. Sequence #6 keeps the aperture inside tolerance with 2% less heat input than the standing sequence.
-
04
weld.sequence
SUCCEEDED
3 m 12 s
Weld-and-Structure · Recommended sequence #6 and the matching clamping plan to the shell line. Seam vision and laser-tracker geometry confirmed the roof-to-sidewall joints inside the control-plan tolerance on the first four seams.
-
05
approve.human
APPROVAL
52 s
Plant Orchestrator · Sequence #6 lowers heat input on the roof joints 2% below the standing weld procedure. Heat-input changes stay with a named engineer, so the step was held for the shift weld engineer and approved at 06:12:44 with the twin evidence attached.
-
06
bogie.torque
SUCCEEDED
continuous
Bogie-and-Running-Gear · Press-fit curves and torque traces on bogie B-14 read at the station. Two traction-motor mounting traces fell outside the expected profile and were routed to rework before brake test; the remaining safety-critical joints verified to spec.
-
07
coat.cure
SUCCEEDED
continuous
Coat-and-Livery · Booth 2 humidity and temperature, film thickness and flash time watched through the livery pass. One masking misalignment on the door band flagged by booth vision before the second coat; the cure window held and handed to the sequence as a hard constraint.
-
08
marry.align
SUCCEEDED
2 m 05 s
Marry-and-Couple · Carbody and bogie scans compared against target interface geometry before the lift. Fit-out readiness confirmed by Fitout-and-Interior for doors and glazing. Marriage guided inside tolerance; coupler and gangway checks verified and written to the twin.
-
09
inspect.fuse
SUCCEEDED
continuous
Quality-and-Anomaly · Weld and coating vision, in-line metrology, torque, wiring continuity and brake-test results fused at the edge across the car. Every finding localised to station, work package and shift, with the two torque reworks and the masking flag already closed.
-
10
car.release
SUCCEEDED
1 m 30 s
Conformance · Car 07 released: genealogy written (weld records per joint, geometry scans, torque traces, coating recipe and cure record, fit-out checks, marriage interface, approvals, test results) and dispositioned against the control plan and IRIS / ISO/TS 22163 criteria with cited evidence for the quality engineer's sign-off.
Market
The market
Figures are the company's own estimates.
$32BTotal addressable spend: carbody, coating and final-assembly automation, welding and coating robotics, geometry control, in-line metrology and vision, MES and line sequencing, train and plant twin software
$8BServiceable with Railira's product and go-to-market
$460MRealistically obtainable within three years, an estimate
~11%Estimated annual growth of the addressable spend
Team
Who is building it
Railira is led by its founder and CEO, Michael Ashford, and its CTO, Scott Reynolds. The profiles below describe what each of them owns and the ground they cover.
Founder & CEO
Michael Ashford
Michael runs the company and owns the design-partner relationships, the pilot structure and the commercial model. He decides which rolling-stock plant and which production stage go first, what weld-quality, rework, dimensional-accuracy or takt number a pilot is judged on, and who at the plant signs off on the baseline.
Focus: rail rolling-stock manufacturing operations, plant economics, OEM and supplier partnerships, and go-to-market.
CTO
Scott Reynolds
Scott owns the line-edge runtime, the carbody and bogie welding, fit-up, coating and takt models, the weld and dimensional inspection, the as-built vehicle digital twin, and the audit architecture behind every Railira agent. He is accountable for the bounded, logged write-back into welding robots and line controls, and for every agent starting in shadow mode.
Focus: edge computer vision, welding robotics and control, simulation and digital twins, safety-critical industrial software.
Hiring
The founding roles we expect to open are on the careers page: edge perception, controls and OT integration, simulation, and a rail manufacturing or quality engineer.
Writing
Recent from the blog
A stopped line rents by the minute
A rolling-stock plant is a chain of tightly coupled, safety-critical steps, and the line that joins them costs tens of thousands of dollars a minute when it stops.
Autonomy is a dial, not a switch
A rolling-stock plant does not go from manual to unattended in one step, and a weld procedure should not be the first thing an agent changes.
Hit quality and takt before the shift
Plants commit a shell, a bogie and a booth to a car before they know the geometry will fit or the cure window will hold. The twin changes the order.
Accelerated computing
Physical AI, at the station
A seam is welded in seconds and a booth cannot wait for the cloud. Perception has to be local, deterministic and fast, so Railira runs GPU inference at the plant edge and keeps training, simulation and optimisation in the cloud or on-prem.
Edge perception
8 to 32 cameras per process area plus metrology, torque, thermal, robot and booth-instrument streams fused at the plant edge. Sub-50 ms weld and seam alerts and sub-150 ms coating and metrology prompts are the design targets. Jetson Thor is planned for higher sensor density.
Model serving
Weld-defect, geometry-risk, coating-risk, point-cloud and takt-risk models served at the plant edge with per-model versioning and rollback, routed by latency, tenant, sensitivity and cost.
Training
Weld and coating defect vision, metrology classification, control-plan reasoning and FEA-surrogate models fine-tuned on plant data and engineer corrections. 100 to 500 GPU-hours per plant during onboarding is the design target; dedicated capacity is planned.
Train-and-plant twin
As-built carbody, coating, marriage and line-flow twin. Weld distortion, geometry build-up, robot reach, coating coverage and layout simulated before the shift. GPU FEA and point-cloud metrology are the workloads; OVX scale is planned.
Synthetic data
Rare weld defects, coating contamination, geometry deviations, occluded seams and torque-escape cases generated and validated against real inspection distributions before promotion. Planned.
Optimisation
Line sequencing, JIS feeding, AMR and AGV routing, buffer management and commissioning-slot scheduling against live readiness.
Robot cells
Robotic weld, coating and assembly cells and AMR or AGV flow; path variants validated in simulation before release to the floor.
GPU ETL
Telemetry features from weld parameters, metrology, coating readings, torque, non-conformance and takt history for retraining, drift detection and network analytics.
Guardrails
An agent that can change a weld sequence needs a leash
Railira writes to production systems. Every capability is scoped, every write is policy-checked against the approved control plan, and every action is written to an append-only audit log the plant owns.
- Bounded action space. Each agent acts only through an explicit tool allow-list, inside per-tool rate and magnitude limits and the approved control-plan envelope for the car type.
- Policy engine before every write. Autonomy level, shift, car type, interlock state and operator presence are evaluated before a recommendation becomes a write to a robot, MES, torque tool or work package.
- Human-in-the-loop gates. Heat-input and weld-sequence changes, schedule release and car release wait for a named approver. High-risk changes remain human-approved until IRIS, plant and OEM acceptance is earned.
- Immutable audit log. Append-only and exportable. Every action records source evidence, the control-plan envelope, confidence, estimated quality and takt impact, rollback path, approver and car scope.
- Hard fallback. Loss of the edge node, the network or a model returns control to the robot, PLC or station's last known-good state. Safety systems and interlocks are never in Railira's path.
- Tenant and program isolation. Designs, control plans, program data, models and memory never cross a customer boundary. On-prem and plant-edge deployment is available for regulated plants.
Compliance posture
| Item | Scope | Status |
|---|---|---|
| SOC 2 Type I and OEM cyber review | Cloud control plane | QUEUED Planned, first 6 months |
| SOC 2 Type II | Cloud control plane | QUEUED Planned, 6 to 12 months |
| SSO and RBAC | Console and approvals | QUEUED Planned, 6 to 12 months |
| IRIS and regulatory assurance packages | Disposition and genealogy evidence | QUEUED Planned, 6 to 12 months; not a certification claim |
| Standards-cited reasoning | Control plans, EN 15085, IRIS / ISO/TS 22163, TSI, AAR, APTA, torque and brake-test procedures | RUNNING In the design, every answer cites its source |
| Per-tenant and program isolation | Designs, control plans, models, memory | RUNNING In the design from day one |
| On-prem and plant-edge deployment | Regulated plants | RUNNING Design option |
FAQ
Straight answers
The questions plant directors, body and coating engineers and quality leads ask in the first meeting.
Only within an explicit tool allow-list with per-tool rate and magnitude limits, inside the approved control-plan envelope, and only at the autonomy level your plant has set. Design partners start in shadow mode, where Railira writes nothing. Heat-input and weld-sequence changes, schedule release and car release stay with a named approver.
Control returns to the robot, PLC or station's last known-good state. Railira is a supervisory layer on top of the controllers, safety systems and interlocks you already run, never a replacement for them, so an outage degrades the line to its current way of running, not to a stop.
Recommendations start from the control plan, the work instructions and the twin in the first weeks. Weld, geometry, coating and torque prediction improve as line history and labelled outcomes accumulate per car type. Onboarding is sized at 100 to 500 GPU-hours per plant and 50,000 to 250,000 synthetic images or scan variants per program, all design targets.
Only if you choose cloud training. Designs, control plans, program data, process models and quality records are isolated per tenant and never used to train another customer's models. Fully on-prem deployment at the plant edge is available for regulated plants, and cross-plant learning is planned and waits on data-rights agreements.
You are, the same as with any control strategy, which is why every write is policy-checked, bounded, logged and reversible, and why anything above your risk threshold waits for a named approver. The audit log records the request, the evidence, the envelope applied and the human decision.
A paid pilot on one process or line area, scoped to a single wedge with a success metric written into the order form: weld or coating rework reduction, geometry escapes, torque escapes, line stoppage minutes or first-time-through. It starts in shadow mode against a baseline from your own records, moves to assist mode when the engineer is satisfied, and expands only after the number moves.