Physical AI · Forging autonomy

The forge runs itself. You decide how far.

Forgiron is an agent operating system for forging and press-forming plants. Specialist agents control billet heating and heat-treat, the press and hammer stroke, and die lubrication and life, watched by fused vision, thermal, ultrasonic and MPI inspection, rehearsed on an as-forged twin, and bounded by a policy engine you control.

Book a cell review See the platform

SUCCEEDED run_7c2e41 scenario complete10 steps · 1 approval gateCell F-2 · 2,500 t press

run_7c2e41 · agent graph · cell F-2 · scenario 10 nodes · 1 approval gate
01 · orchestrator ingest.order ✓ SUCCEEDED 02 · forgetwin twin.simulate ✓ SUCCEEDED 03 · heat_billet heat.soak ✓ SUCCEEDED 04 · die_lube die.spray ✓ SUCCEEDED 05 · orchestrator approve.human ◆ APPROVAL 06 · forge_press forge.stroke ✓ SUCCEEDED 07 · defect_inspect inspect.fuse ✓ SUCCEEDED 08 · robot_handling handle.transfer ✓ SUCCEEDED 09 · trim_heat heat.treat ✓ SUCCEEDED 10 · quality_conf lot.release ✓ SUCCEEDED

Illustrative scenario: Cell F-2 · 2,500 t closed-die press · 42CrMo4 connecting rod, one lot, one approval gate

Design partners wanted · 3 to 5 forges · cells we are looking for

Induction billet heating Closed-die press cells Hammer and upsetting lines Ring rolling Heat-treat lines Ultrasonic and MPI inspection

Pre-launch. No customers, pilots or logos are claimed. The first cohort gets a paid pilot on one cell against a baseline agreed in writing.

Run timeline · scenario

One scenario run, step by step

Every Forgiron run is an ordered, inspectable sequence. This is run_7c2e41 on Cell F-2 · 2,500 t closed-die press · 42CrMo4 connecting rod. Scenario completes in 10 steps with one approval gate. Surface temperature held at 1,205 °C with a 14 °C core-to-surface spread, fill predicted and confirmed complete, one lap precursor at the flash land cleared by a blow-energy trim, lot L-80412 released with full genealogy.

run_7c2e41 Cell F-2 · 2,500 t closed-die press · 42CrMo4 connecting rod illustrative scenario SUCCEEDED
  1. 01 ingest.order SUCCEEDED 0.6 s

    Plant Orchestrator · Pulled the part spec for the 42CrMo4 connecting rod from MES: forging window 1,180 to 1,230 °C, two-blow closed-die schedule, flash land 2.4 mm, temper to 28 to 32 HRC, 1,200 pieces. Locked the qualified process envelope.

  2. 02 twin.simulate SUCCEEDED 52 s

    Forge Twin · Simulated 24 candidate heat-and-stroke recipes on the as-forged twin for soak time, blow energy and spray timing, ranked on predicted fill, lap risk at the flash land, die load and kWh per piece.

  3. 03 heat.soak SUCCEEDED 2 m 10 s

    Heat-and-Billet · Induction power on IH-2 stepped down 4% in the final soak stage as the pyrometer read 1,205 °C at the surface. Core-to-surface spread estimated at 14 °C against a 20 °C limit, no overheat, scale growth inside the window.

  4. 04 die.spray SUCCEEDED 48 s

    Die-and-Lube · Lower-die spray dose raised 6% and cooling extended 0.3 s as die surface temperature climbed through 240 °C. Heat-check growth on cavity 2 flagged at 0.31 of the die-change threshold.

  5. 05 approve.human APPROVAL 46 s

    Plant Orchestrator · Recipe #9 moves second-blow energy 3% below the standing schedule. Press-schedule changes stay supervised on this part family, so the step was held for the shift forging engineer and approved at 05:47:31.

  6. 06 forge.stroke SUCCEEDED 1 m 36 s

    Forge-and-Press · Two-blow schedule executed with the approved energy. High-speed vision and force curves confirmed complete fill on the first ten pieces; predicted lap risk at the flash land fell from 0.27 to 0.08.

  7. 07 inspect.fuse SUCCEEDED continuous

    Defect-and-Inspect · Eight cameras, two thermal cameras and the ultrasonic station fused at the edge. One lap precursor at the flash land on piece 212 flagged and cleared by a 1.5% blow-energy trim inside the approved envelope; the piece was routed to MPI and passed.

  8. 08 handle.transfer SUCCEEDED continuous

    Robot-and-Handling · Press-to-trim transfer planned and executed by the handling robot at 11 s per piece, temperature loss in transfer 38 °C against a 60 °C limit, interlock zones clear throughout.

  9. 09 heat.treat SUCCEEDED continuous

    Trim-and-Heat · Temper furnace HT-1 zone 2 trimmed 5 °C against the predicted hardness from the recorded heat and stroke history. First hardness checks read 30 HRC, inside 28 to 32.

  10. 10 lot.release SUCCEEDED 1 m 20 s

    Quality-and-Conformance · Lot L-80412 released: genealogy written (billet lot, heat curve, stroke record, die cycles, inspection map, approvals, temper record) and dispositioned against IATF 16949 criteria with cited evidence for the quality engineer's sign-off.

Tool calls · scenario

The agent shows its work

Every tool invocation, argument and result is written to an append-only, human-readable log, and every reasoning step is expandable. Nothing about a run is hidden from the forge.

tool-call stream · run_7c2e41
  1. 05:40:02mes.read_order({ cell: "F-2", part: "CR-42CrMo4-118", qty: 1200 })
  2. 05:40:02ok envelope locked · 1,180 to 1,230 °C · 2 blows · 28 to 32 HRC
  3. 05:40:03twin.simulate({ candidates: 24, horizon: "1 lot" })
  4. 05:40:55ok best recipe #9 · fill 1.00 · lap risk 0.08 · 1.9 kWh/pc
  5. 05:40:56policy.evaluate({ recipe: 9, autonomy: "L2+" })
  6. 05:40:56ok 7 writes permitted · press_schedule requires human approval
  7. 05:40:57induction.set_power({ tag: "IH2.STAGE3_KW", delta: "-4%" })
  8. 05:43:07ok surface 1,205 °C · core-to-surface spread 14 °C · no overheat
  9. 05:43:08spray.set_dose({ die: "F2.LOWER", dose: "+6%", cool: "+0.3 s" })
  10. 05:43:56ok die surface 240 °C · heat-check index 0.31
  11. 05:43:57approval.request({ action: "press_schedule", blow2: "-3%" })
  12. 05:47:31ok approved by shift forging engineer · logged
  13. 05:47:32press.set_schedule({ press: "F-2", recipe: 9 })
  14. 05:49:08ok fill complete on 10 pieces · lap risk 0.27 → 0.08
  15. 05:49:09sensors.fuse({ cams: 8, thermal: 2, ut: true })
  16. 06:21:40precursor: lap risk 0.52 · flash land · piece 212
  17. 06:21:41press.set_schedule({ press: "F-2", blow2: "-1.5%", within: "approved envelope" })
  18. 06:21:58ok lap risk 0.52 → 0.07 · piece 212 routed to MPI · passed
  19. 06:22:00isaac.plan_path({ task: "press_to_trim", cell: "F-2" })
  20. 06:22:11ok 11 s per piece · transfer loss 38 °C · zones clear
  21. 06:22:12furnace.set_zone({ furnace: "HT-1", zone: 2, delta: "-5 °C" })
  22. 06:58:40ok first hardness 30 HRC · inside 28 to 32
  23. 06:58:41mes.log_forging({ lot: "L-80412", genealogy: "full" })
  24. 07:00:01ok scenario complete · 10 steps · 0 laps escaped · released

Reasoning trace

Plan, thought, action, observation, exactly as the orchestrator would record it.

GoalRun the 42CrMo4 connecting-rod lot on cell F-2 inside the qual…

Run the 42CrMo4 connecting-rod lot on cell F-2 inside the qualified window, hold full fill with zero laps at the flash land, and land hardness between 28 and 32 HRC.

PlanSimulate heat-and-stroke recipes on the twin first. Lead with …

Simulate heat-and-stroke recipes on the twin first. Lead with heating so the billet state is right before the stroke, then set spray against die temperature, then execute the approved press schedule. Fuse inspection continuously. Hold any press-schedule change for a human.

ThoughtThe standing schedule runs the second blow hot enough to guara…

The standing schedule runs the second blow hot enough to guarantee fill on a cold billet. With the induction soak held at 1,205 °C the twin predicts the same fill at 3% less energy and lower flash-land lap risk, because the metal arrives more uniform.

Actiontwin.simulate(candidates=24) returns recipe #9: stage-3 induct…

twin.simulate(candidates=24) returns recipe #9: stage-3 induction power down 4%, lower-die spray up 6%, second-blow energy down 3%.

ObservationRecipe #9 predicts fill 1.00, lap risk 0.08 and 1.9 kWh per pi…

Recipe #9 predicts fill 1.00, lap risk 0.08 and 1.9 kWh per piece. Two candidates scored lower on energy but pushed predicted die load past the cavity-2 limit and were discarded.

ActionExecute recipe #9: seven bounded writes permitted on heating, …

Execute recipe #9: seven bounded writes permitted on heating, spray, handling and heat-treat; the press-schedule write routed to the shift forging engineer.

ObservationLap precursor at the flash land on piece 212 at 06:21:40. A 1.…

Lap precursor at the flash land on piece 212 at 06:21:40. A 1.5% blow-energy trim inside the approved envelope cleared it in 17 s; the piece was routed to MPI and passed.

OutcomeScenario complete. Fill confirmed, no laps escaped, hardness 3…

Scenario complete. Fill confirmed, no laps escaped, hardness 30 HRC. Lot L-80412 released with full genealogy.

How it works

A goal becomes a plan becomes a run

Nothing about a Forgiron run is implicit. The goal is declared, the plan is simulated on the twin, each step is typed and bounded, and the outcome is written to the forging's genealogy.

Active path

The orchestrator plans, the agents act

A run starts as a goal, becomes a plan, and executes as a graph of typed steps. The active path is always visible, always logged, always reversible.

RUNNING APPROVAL SUCCEEDED
<100 ms edge inference for visual defect alerts · design target
<500 ms decision latency for non-emergency process recommendations · design target
8 to 24 cameras per line, with 10 to 50 Hz thermal streams · design target
100 to 1,000 Hz press, ram and force telemetry rate · design target
Human in the loop

Autonomy is a dial, not a switch

L1 shadow, L2 assist, L3 bounded autonomy on low-risk actions, L4 supervised press-schedule adaptation for qualified part families. Each forge sets the level per agent, per tag, per shift, and every write above the threshold waits for a named approver. The four figures above are design targets, not measured results.

Agent roster

Ten agents, a twin and an orchestrator

Each agent owns a step of the forge, a bounded tool set and a metric the plant already measures. They negotiate for shared actuators through the orchestrator, never directly. Six named products ship them.

agent.heat_billet · shipped as Heatrix

Heat-and-Billet

Induction and furnace billet heating, temperature, soak

Senses billet temperature, core-to-surface spread, soak and furnace or induction state from thermal imaging, pyrometry and coil or burner telemetry, predicts what the thermal state will do to fill, grain flow and properties downstream, and adapts induction power, furnace zones and soak time to hit forging temperature at minimum energy without overheating or decarburization.

pyro.read_surfaceinduction.set_powerfurnace.set_zone

agent.forge_press · shipped as Forgeon

Forge-and-Press

Press and hammer stroke, force, ram speed, die fill, grain flow

Senses press or hammer force, stroke, energy, billet position and die fill in real time, predicts fill, grain flow and lap, fold or underfill risk from the incoming thermal state, and adapts stroke schedule, blow energy and ram speed to hit target fill and grain flow at minimum blows and energy. Stroke-schedule changes stay supervised until the part family is qualified.

press.read_forcepress.set_schedulevision.read_fill

agent.die_lube · shipped as Diesmith

Die-and-Lube

Die temperature, wear, heat-checking, lubrication, cooling

Models die temperature, wear and heat-checking from thermal and vision, predicts remaining die life and thermal-fatigue risk, and controls lubricant dosing, spray and die cooling to hold friction and fill while scheduling die changes and refurbishment before they seed underfill, laps or dimensional drift.

thermal.read_diespray.set_dosedie.schedule_change

agent.trim_heat

Trim-and-Heat

Trimming, heat treatment, finishing to hardness and properties

Carries the thermal loop past the press: trimming, austenitize, quench and temper, and finishing, controlled to hardness and mechanical-property targets. The heat-treat loop is delivered through Heatrix; trimming and finishing are part of the platform.

furnace.set_zonequench.set_profilehardness.read

agent.defect_inspect · shipped as Flawnex

Defect-and-Inspect

Laps, folds, underfill, cracks and internal defects

Fuses vision, ultrasonic, MPI, thermal and dimensional data into one model of forging soundness. Detects and predicts laps, folds, underfill, cold shuts, surface cracks and internal defects, routes suspect parts for ultrasonic, MPI or dimensional checks, and couples each finding back to the heat, stroke and die state that caused it.

sensors.fuseut.read_scanmpi.read_indication

agent.quality_prop · shipped as Flawnex

Quality-and-Property

Grain flow, hardness, mechanical properties, dimension

Models grain flow, hardness and mechanical properties against the part spec from process history, inspection and heat-treat results, and holds dimension after cool-down. It reconciles what the control agents want with what the specification allows.

spec.checkproperty.predictcmm.read_dimension

agent.yield_takt · shipped as Forgetwin

Yield-and-Takt

Yield, scrap, die life, energy, line balancing

Prices every candidate move in scrap, die strokes, kilowatt-hours and minutes, allocates dies, batches heats, sequences press and heat-treat queues and balances the moving line against robot availability and downstream capacity.

cuopt.sequencemes.read_ordersenergy.budget

agent.robot_handling · shipped as Forgebot

Robot-and-Handling

Hot billet, forging and die handling

Drives robotic and manipulator handling of hot billets, forgings, dies and trim parts, perceiving pose, temperature and grip, planning safe paths around presses and furnaces, and coordinating takt so parts arrive at the right station at the right temperature. Skills are validated in Isaac Sim before they run near a press.

isaac.plan_pathgripper.set_posesafety.check_zone

agent.quality_conf

Quality-and-Conformance

Right-first-time, non-conformance, genealogy, qualification

Builds the forging genealogy record per part and lot, dispositions against AS9100, IATF 16949, NADCAP and ASTM criteria with cited evidence, and assembles the packets a quality engineer signs for customer, first-article and qualification review.

mes.log_forgingdisposition.writeaudit.write

agent.forge_knowledge

Forge-Knowledge

Recipes, die history, standards, operator Q&A

Answers process, metallurgy and standards questions from heating and press recipes, die and forging specs, AS9100, IATF 16949, NADCAP and ASTM documents and quality procedures, with every answer cited to its source and scoped to the tenant.

rag.retrievestandards.citeprocedure.lookup

twin.forgetwin · shipped as Forgetwin

Forge Twin

As-forged part and forge-line simulation

Simulates billet heating, die thermal state, press stroke, fill, stress, die load, trim and heat-treat with GPU-accelerated forging FEM, compares as-forged against as-designed, and auto-optimises the heating, press-schedule and die setpoints the other agents execute so the part hits soundness, dimension and takt before the stroke.

twin.simulatetwin.compare_asforgedrecipe.optimise

agent.orchestrator

Plant Orchestrator

Planning, arbitration, human approval

Plans the run, arbitrates between agents competing for the same actuator, enforces the autonomy level and routes anything above the risk threshold, press-schedule changes first among them, to a named approver.

plan.composepolicy.evaluateapproval.request
Where it pays

Four loops, four metrics

Forgiron is not a dashboard. Each agent closes a loop a forge already measures in scrap, die changes, kilowatt-hours and inspection escapes. The tables show what each loop watches and what it is allowed to move.

Heating and energy

Hit forging temperature at the least kWh

Thermal imaging, pyrometry and coil telemetry are fused at the edge into a live estimate of surface temperature, core-to-surface spread and soak. Heatrix adapts induction power and furnace zones to land the window without overheating or decarburization, and prices every heat in kilowatt-hours.

  • Surface and core state estimated continuously, not from a spot thermocouple
  • Per-alloy thermal windows enforced at call time
  • Every heat labelled with its downstream fill and property outcome
agent.heat_billet SUCCEEDED
SignalWatchesMoves
Billet temperaturePyrometer and thermal cameraInduction power, furnace zones
Core-to-surface spreadEstimated from heating curveSoak time
Energy per heatCoil and burner telemetryStage power inside the window
Fill and grain flow

Decide the stroke before the ram drops

Force curves, ram position and high-speed vision are fused with the incoming heat state. Forgeon predicts fill, grain flow and lap or underfill risk per piece and proposes the stroke schedule that hits them at minimum blows and energy, validated on the twin and approved by the forging engineer until the part family is qualified.

  • Fill and lap risk predicted from heat and geometry, not judged after cooling
  • Blow energy and ram speed moved together
  • Press-schedule changes supervised by a named engineer
agent.forge_press SUCCEEDED
SignalWatchesMoves
Die fillForce curve and high-speed visionBlow energy, ram speed, under approval
Lap and underfill riskScored per pieceEnergy trim inside the approved envelope
Grain flowModelled from stroke scheduleSchedule candidates ranked on the twin
Die life

Pull the die before it scraps a part

Die surface temperature, heat-check growth and lubricant coverage are modelled from thermal and vision between strokes. Diesmith doses spray and cooling to hold friction and fill and schedules the die change in a planned window instead of after the first underfill.

  • Die life predicted per cavity
  • Spray and cooling controlled between strokes
  • Die changes scheduled, not reacted to
agent.die_lube SUCCEEDED
SignalWatchesMoves
Die temperatureThermal camera between strokesSpray dose and cooling
Heat-check growthVision per cavityDie-change window
Lubricant coverageVisionSpray pattern and timing
Laps, cracks and internal defects

See the defect and the stroke that made it

Vision, thermal, ultrasonic, MPI and dimensional data are fused into one model of soundness. Flawnex detects and predicts laps, folds, underfill, cracks and internal defects, routes suspect parts to the right check, and couples each finding back to the heat, stroke and die state behind it.

  • Five modalities, one estimate of soundness
  • Defects localised to part, lot, die cavity and stroke
  • Disposition grounded in AS9100, IATF 16949, NADCAP and ASTM with citations
agent.defect_inspect SUCCEEDED
SignalWatchesMoves
Surface laps and cracksCameras and MPIEnergy trim via Forgeon, part routing
Internal defectsUltrasonic stationLot hold, root cause to heat and stroke
Dimension after cool-downDimensional scanSpec envelope to the control agents
Multi-agent handoff

Agents negotiate, they do not collide

Two agents will want the same actuator. The orchestrator arbitrates on the run goal, not on who asked first, and the handoff is logged like any other step.

Contested move: F-2 second-blow energy

  1. 01yield_takt.request(blow2 −1.0%) SUCCEEDED0.2 s

    Yield-and-Takt wants to trim second-blow energy to cut kWh per piece and die load on cavity 2.

  2. 02defect_inspect.request(blow2 +1.5%) SUCCEEDED0.2 s

    Defect-and-Inspect wants to raise second-blow energy to clear a lap precursor at the flash land on piece 212.

  3. 03orchestrator.arbitrate SUCCEEDED0.4 s

    Lap risk 0.52 outranks 1.0% of energy under the run goal "zero laps at the flash land". Defect-and-Inspect wins the actuator for 40 pieces, inside the approved envelope.

  4. 04yield_takt.handoff(returned) SUCCEEDED40 pcs

    Actuator returned. Yield-and-Takt recovers energy through the induction soak stage instead. Fill holds complete.

Illustrative scenario.

Arbitration rules

  • Run goal first. Every request is scored against the declared goal, not the requesting agent's local objective.
  • Soundness outranks yield. A lap on a safety-critical forging costs more than a percent of energy.
  • The envelope is never contested. Both requests must sit inside the approved process envelope; anything outside goes to a human.
  • Time-boxed ownership. An agent holds a contested actuator for a bounded number of pieces, then must re-justify.
  • Everything is logged. The losing request, the score and the reason all appear in the run record.
  • Deadlocks escalate to a human rather than resolving by timeout.

See the agent roster

Autonomy

Four levels, set per agent and per tag

A forge does not go from manual to unattended in one step. Forgiron makes the level explicit, auditable and reversible at any time. The first release runs shadow mode, then assist mode, then bounded autonomy on low-risk actions. Press control stays supervised until the part family is qualified.

Autonomy levels and the human role at each
LevelWhat the agent doesWhat the human doesWhere it sits in a pilot
L1 · ShadowReads thermal, vision, ultrasonic, MPI, press, die, robot and MES signals; predicts and recommends; writes nothingRuns the cell as today; compares predictions to inspection and engineer outcomesShadow mode, baseline 30 to 60 days
L2 · AssistProposes heating, press, die-lube, routing and handling actions with evidence, confidence, envelope and rollback pathApproves each action in the review consoleAssist mode, the remainder of a 90 to 180 day pilot
L3 · BoundedExecutes pre-approved low-risk actions: inspection routing, lube timing, heating and soak adjustments, robot path variants, inside PLC and safety limitsApproves press-schedule changes, die changes and lot releaseGraduated autonomy, after audited accuracy and ROI
L4 · ScaledSupervised press-schedule adaptation for qualified part families, across cells and sitesSets the envelope; reviews the shift record and the evaluation resultsPlanned; after golden-dataset evaluation, simulation validation and quality sign-off
Targets

Design targets, stated as targets

These are the figures in our compute plan. None is a measured result. Every pilot measures against the forge's own baseline, reproduced from the plant's own scrap, die and inspection records, not from our telemetry.

2 M labelled frames and signals per design-partner cohort · design target
20,000 heat and press cycles in the first training sets · design target
10,000 die-life events and 5,000 inspected defect outcomes · design target
100,000 synthetic defect and die-wear scenarios per priority part family · design target
Segments

Where forges start

Automotive and driveline, aerospace and defense, energy, industrial forgings, ring rolling and open-die. Most forges pick one cell and one wedge, prove the number, then expand.

Automotive and drivelineVolume, scrap and die cost

Automotive and driveline

Crankshafts, connecting rods, gears, axle and suspension parts at rate. Heatrix and Diesmith on the highest-volume cell first, where scrap and unplanned die changes are already counted.

Aerospace and defenseQualification burden

Aerospace and defense

Turbine and engine discs, landing gear and structural forgings under AS9100 and NADCAP. Flawnex on the inspection line, with genealogy and cited disposition from day one.

EnergyHigh part value

Energy

Turbine, oil and gas and nuclear forgings where a single internal defect is catastrophic. Flawnex and Forgetwin on the part family with the longest qualification cycle.

Industrial forgingsValves, flanges, fittings

Industrial forgings

Closed-die and upsetting lines making industrial parts in many alloys. Forgeon and Diesmith on the press cell with the most changeovers.

Ring rolling and open-dieLarge sections, long heats

Ring rolling and open-die

Rings and open-die forgings where billet heating is the energy bill and the stroke count is high. Heatrix first, then Forgeon on the mill.

Accelerated computing

Physical AI, at the press

A stroke lasts a fraction of a second and a billet cools while it waits. Perception has to be local, deterministic and fast, so Forgiron runs GPU inference at the plant edge and keeps training, simulation and optimisation in the cloud or on-prem.

Jetson Orin · DeepStream · Holoscan · TensorRT

Edge perception

8 to 24 cameras per line plus thermal, ultrasonic, MPI, press and ram streams fused at the cell. Sub-100 ms visual alerts and sub-500 ms recommendations are the design targets. Jetson Thor is planned for higher sensor density.

Triton · NIM

Model serving

Defect, ultrasonic and MPI fusion, die-wear, heating, press-fill, property and disposition models behind one orchestrator at the plant edge, routed by latency, tenant, sensitivity and cost, with canary rollout by cell.

DGX or HGX · NeMo

Training

Multimodal defect, die-wear, heating, press-fill, property and quality-disposition models trained on thermal images, high-speed vision, ultrasonic and MPI signals, press curves and engineer corrections. Dedicated training capacity is planned.

Omniverse · OVX · Modulus

Forge-line twin

Billet heating, die thermal state, press stroke, fill, stress, die load and robot handling simulated before the stroke. GPU forging FEM is the workload; physics-informed surrogates are planned so recipes rank at production cadence.

Cosmos · Omniverse Replicator

Synthetic data

Rare lap, fold, underfill, crack and die-wear scenarios generated and validated against real inspection distributions before promotion. Planned.

cuOpt

Optimisation

Die allocation, press sequencing, heating batches, heat-treat queues, robot and takt coordination and inspection routing.

Isaac Sim · Isaac Lab · Isaac ROS

Robot handling

Hot billet, forging, die and trim handling skills trained and validated in simulation before they run next to a press.

RAPIDS

GPU ETL

Daily features from thermal, video, ultrasonic, MPI, press and genealogy data for retraining, drift detection and yield, scrap, die-life and energy benchmarks.

Developers

Define an agent, bound it, run it

The Forgiron SDK is typed Python. Tools are declared with schemas, limits and the qualified process envelope, and the policy engine enforces them at call time, not in a review meeting. This is a design preview; the API will change before release.

What you get

  • Typed tool definitions with unit-aware ranges, rate limits and process envelopes
  • Deterministic replay of any historical run against a new model
  • Local twin harness so a recipe is simulated before it is shipped
  • Autonomy policy as code, versioned and reviewed like any other change

Read the docs Developer guide

f2_heating_agent.py 
# Design preview. Bound the heating agent to induction heater IH-2.
from forgiron import Agent, Tool, Limit, Autonomy

power = Tool(
    name="induction.set_power",
    tags=["IH2.STAGE3_KW", "IH2.SOAK_S"],
    limits=[Limit(max_step="4%", per="60s", envelope="42CrMo4-CR118")],
)

heat = Agent(
    id="agent.heat_billet",
    goal="surface 1180 to 1230 C, core-to-surface spread <= 20 C, least kWh",
    tools=[power, Tool("pyro.read_surface", read_only=True)],
    # bounded writes on heating; press schedule stays with a human
    autonomy=Autonomy.L3,
    # simulate on the twin before every write
    verify="twin",
)

run = heat.start(cell="F-2", part="CR-42CrMo4-118")
for step in run.stream():
    print(step.name, step.status, step.duration)
CLI

Start a run from anywhere

The same run engine, the same policy checks, the same audit trail, from the terminal, the review console or the SDK. Design preview.

forgiron · cli · scenario 
$ forgiron run "lot CR-42CrMo4-118 on F-2" --autonomy L2+

→ plan composed          10 steps · 1 approval gate
→ twin.simulate          24 candidates · best #9 · lap risk 0.08
→ policy.evaluate        7 writes permitted · press_schedule held for human
→ executing              heat.soak ........ ok   2m10s
→ executing              die.spray ........ ok   48s
! approval required      press_schedule blow2 −3%
→ approved               shift forging engineer · 05:47:31
→ executing              forge.stroke ..... ok   1m36s
→ executing              inspect.fuse ..... ok   continuous
→ scenario complete      laps escaped 0 · lot L-80412 released

$ forgiron runs show run_7c2e41 --format genealogy
Pricing

Priced per cell, per plant, per group

Land on one workflow with a measured baseline. Expand by cell, module and autonomy level. Outcome components are available on yield, scrap, die life and energy. Annual prepay carries a 15 to 20% discount.

Cell $15,000 per forging or heat-treat cell or line / month · billed monthly

Heating or forging control, die management, or inspection AI for one cell. For forges validating ROI on the wedge.

  • One cell, one agent module
  • Plant-edge inference node included
  • Controller and sensor reads, guarded writes
  • Run log, audit trail, forging genealogy
  • Business-hours support
Start a pilot
Recommended Plant $90,000 per plant / month · billed monthly

The whole forge: heat and billet, forge and press, die and lube, trim and heat-treat, defect, quality and property, yield and takt, robotic handling and the twin.

  • All control agents on every cell
  • Fused inspection on every line
  • Quality, property, yield, takt and conformance
  • Robotic billet, forging and die handling
  • As-forged twin and line sequencing
  • 24/7 support, quarterly model review
Talk to us
Enterprise Custom land $650k to $8.5M ACV

Multi-site forging groups standardising on Forgiron, with custom alloy, die and qualification models.

  • Multi-site fleet management
  • Custom alloy, die and qualification models
  • Plant edge fleet with on-prem option
  • Group autonomy policy and approval chains
  • SLAs, SSO and RBAC, dedicated engineer
Contact us
Who it is for

Built for the people who run the forge

We have no customer quotes to show yet and will not invent any. These are the three roles in a forge we build for, and the problems they bring to the first meeting.

Plant or Operations Director

Owns production rate, quality, scrap and yield, die life, energy and safety.

What this person is dealing with today

  • Fixed heating and press setpoints that cap fill, grain flow, rate and consistency
  • Scrap, downgrade, die changes and energy eroding margin in a brutal, hot environment
  • A severe, retiring forge-operator and die-engineer shortage that caps rate

Forging or Die Engineer

Owns heating, press schedules, die design and heat-treat recipes, process windows and yield.

What this person is dealing with today

  • Laps, folds, underfill, cracks and internal defects driving scrap and downgrade
  • Die wear and thermal fatigue forcing costly die changes and downtime
  • Heating, forging, die management and inspection siloed and reactive

Quality or Reliability Engineer

Owns forging quality to AS9100, IATF 16949, NADCAP and ASTM, defect and grain-flow conformance, genealogy and qualification traceability.

What this person is dealing with today

  • Overheating, decarburization and heat-treat faults degrading properties and safety
  • Spot inspection by a scarce NDT workforce, with escapes that become field failures
  • Qualification evidence assembled by hand after the fact
Integrations

It speaks forge, not cloud

Forgiron reads and writes through the systems already on the floor. No rip and replace, no parallel historian, no new HMI to learn. Vendor names are examples of systems found in forges, not certified integrations; connector availability is confirmed per site.

Billet heating

Induction and furnace PLCs (EFD Induction, Ajax TOCCO, Inductotherm, SMS group class systems)

Power, zone and soak reads, guarded writes

Presses and hammers

Press, hammer and ring-mill controls (SMS group, Schuler, Ajax, Sumitomo and Nedschroef, Danieli class systems)

Force, ram and energy reads; supervised schedule writes

Die spray and cooling

Spray, lubrication and die-cooling systems

Dose, pattern, timing and cooling

Thermal and vision

Thermal cameras, pyrometers, high-speed cameras at the press

Billet and die temperature, fill, surface defects

Ultrasonic, MPI, dimensional

Ultrasonic and MPI stations and dimensional systems (Waygate, Evident, Magnaflux class systems)

Scans, indications and dimensions per part

Forging simulation

Forging FEM packages (Transvalor Forge, Simufact Forming, QForm, DEFORM class tools)

Model and result exchange with the twin

Robots and safety

Robots, manipulators and safety PLCs

Pose, grip and path state inside interlocked limits

Heat-treat

Austenitize, quench and temper furnaces

Zone, quench and temper reads, guarded writes

See all integrations

Guardrails

An agent that can move a press schedule needs a leash

Forgiron writes to production equipment. Every capability is scoped, every write is policy-checked against the qualified envelope, and every action is written to an append-only audit log the forge owns.

  • Bounded action space. Each agent writes only to an explicit tag allow-list, inside per-tag rate and magnitude limits and the qualified process envelope for the part family.
  • Policy engine before every write. Autonomy level, shift, part family, interlock state and operator presence are evaluated before a setpoint moves.
  • Human-in-the-loop gates. Press-schedule changes, die changes and lot release wait for a named approver. Safety-critical press control stays guarded by PLC interlocks and engineer approval until qualification evidence supports more.
  • Immutable audit log. Append-only and exportable. Every action records source evidence, the approved process envelope, confidence, estimated yield, scrap, die-life and energy impact, rollback path, approver and lot scope.
  • Hard fallback. Loss of the edge node, the network or a model returns control to the furnace, press or die controller's last known-good state. Interlocks are never in Forgiron's path.
  • Tenant and die-IP isolation. Die designs, part drawings, alloy recipes and quality records never cross a customer boundary. On-prem deployment is available for sensitive producers.

Compliance posture

ItemScopeStatus
SOC 2 Type ICloud control plane QUEUED Planned, first 6 months
SOC 2 Type IICloud control plane QUEUED Planned, 6 to 12 months
SSO and RBACConsole and approvals QUEUED Planned, 6 to 12 months
AS9100 and NADCAP assurance packagesDisposition and genealogy evidence QUEUED Planned, 6 to 12 months; not a certification claim
Standards-cited reasoningAS9100, IATF 16949, NADCAP, ASTM documents RUNNING In the design, every answer cites its source
Per-tenant and die-IP isolationRecipes, die designs, models, memory RUNNING In the design from day one
On-prem and plant-edge deploymentSensitive producers RUNNING Design option

Read the security overview

Enterprise

Standardise autonomy across the group

One policy model, one audit trail, one benchmark across every cell in every forge, with the alloy, die and qualification models kept private to each site.

Talk to us Enterprise details

  • SSO and role-based access down to the tag level, planned for the 6 to 12 month release
  • Group-wide autonomy policy with per-site override and approval chains
  • Cross-plant benchmarking on yield, scrap, die life, energy and inspection escapes
  • On-prem and plant-edge deployment, with air-gapped operation for defense and sensitive producers
  • Edge autonomy that survives control-plane loss by returning to the controller's last known-good state
  • Dedicated deployment engineer and quarterly model review per forge
FAQ

Straight answers

The questions plant directors, forging engineers and quality engineers ask in the first meeting.

Yes, but only within an explicit tag allow-list with per-tag rate and magnitude limits, inside the qualified process envelope, and only at the autonomy level your plant has set. Design partners start in shadow mode, where Forgiron writes nothing. Press-schedule changes stay supervised by a named forging engineer until the part family is qualified.

Get started

Bring autonomy to your forge

Start with one heating, press, die or inspection cell and one measurable baseline. A paid pilot on billet heating and press fill, die life or ultrasonic and MPI defect detection shows the number before you commit further.

Book a cell review See pricing