ReuseQualified personality + operating point
DEFAULTLUMA · QUALIFIED AI INFRASTRUCTURE
Run the same accepted AI service on less machine.
LUMA turns your cost, power, capacity and service boundary into a machine requirement, qualifies the states that can satisfy it, then automatically selects, applies, verifies and rolls back those states as operating conditions change.
Available now · Qualification SprintFor AI infrastructure teams with a named model, workload and service target
Economic state authorityResource boundary + qualified-state library + live value verification + rollback authority
Build when the boundary demands itSoftware/runtime → FPGA persona → accelerator/silicon intervention, each admitted by physical and economic evidence
LIVE SERVICE CONTRACT QUALIFIED CONTROL
MODELWeights + semantics
WORKLOADContext · concurrency
CONSTRAINTLatency · power · cost
LUMA CONTROLSmallest sufficient interventionEvidence + service + lifetime economics
SwitchBounded qualified hardware persona
WHEN VALUE > COSTBuildNew hardware capability, qualified offline
EVIDENCE-GATED01Same accepted resultQuality and service are hard constraints.
02Whole-system economicsCards, accepted goodput, power and software burden counted.
03Physical qualificationMeasurement authorizes deployment—not prediction.
04Automatic savings controlSelect, apply, verify, retain or roll back qualified states as value changes.
THE PRODUCT
From buying boundary to controlled machine action.
You give us the model, production workload, SLO, current infrastructure and economic target. LUMA compiles the machine requirement, identifies the binding physical deficit, qualifies the highest-value intervention and turns passing states into an operating library the controller can use.
INPUT
Your actual accepted service.
Model or model pool, quality rules, prompt/context distribution, concurrency, latency targets, deployment constraints, power ceiling and economic objective.
MODEL REVISIONWORKLOAD DISTRIBUTIONTTFT / TPOTPOWER ENVELOPEECONOMIC OBJECTIVE
OUTPUT
A deployable, qualified machine state.
Hardware personality, model program, state layout, runtime/backend, deployment bundle, measured service envelope and normal application-facing API.
{
"model": "qualified-model",
"messages": [...],
"stream": true
}
CONCRETE CUSTOMER HANDOFF
What the first customer-usable release actually contains.
Customer input: named model/revision, production workload distribution, accepted quality/SLO, current infrastructure and the economic boundary that matters.
LUMA return: Resource Boundary Report + qualified machine-state manifest + runtime/backend configuration + synchronized physical evidence + deployment/API bundle. A deeper FPGA persona is admitted only after offline build, place-and-route and physical qualification.
M12 · CUSTOMER RELEASE AFirst customer-usable fixed-FPGA qualification release
Frozen Qwen service + R1-v1 + one qualified FPGA backend path + one selected compute mechanism + L0 apply/observe/verify + TTFT/TPOT/goodput/BW/p99/power/temp evidence + first Resource Boundary Report + deployment/API bundle.
M13 → M36 · RESEARCH GENERATIONSAdaptive personas + physical integration + cross-backend TRL4 closure
Second mechanism generations, state-safe DFX, physical integration, recovery stress, broader workloads, second-backend portability and final TRL4 transfer.
QUALIFIED ADAPTATION
First prove you can remove resources. Then change hardware only when it pays.
LUMA searches qualified operating territory first. Deeper hardware change enters when the service requires it or when the expected machine-count, goodput or energy value repays the intervention.
More power / costLess power / cost
Qualified
Selected
Qualified
Measure first
Current service requirement
Lower service demandHigher service demand
1
Observe
Current workload, state pressure, service demand, thermal and power condition.
2
Contain
Find the qualified operating region that still satisfies every hard service constraint.
3
Minimize
Select the lowest-resource / lowest-cost qualified point for the current demand, counting machine provision, accepted goodput and power.
4
Intervene only when it pays
Switch L1 or build L2 only when expected lifetime value clears transition, build and qualification cost.
ECONOMIC CONTROL PILOT
The savings stay alive after the benchmark ends.
LUMA converts qualified evidence into a live control authority. Demand, context mix, concurrency, power availability and economic coefficients move; the machine state follows inside a prequalified envelope.
LIVE CONTROL CONTRACT
Optimize the customer value function continuously.
The controller observes the current service cell and complete resource vector, scores only physically qualified states, actuates the strongest candidate, probes accepted service and realized value, then commits or rolls back.
Control targets: devices required · sessions/node · wall power · J/accepted output · cost/accepted output · rack/facility envelope.
Order an Economic Control Pilot01ObserveWorkload, service, state pressure, power and current economics.
02SelectHighest-value state inside the qualified evidence envelope.
03ApplyRuntime, board, GPU or FPGA actuation through its bounded contract.
04VerifyAccepted service and realized resource/energy/cost effect.
05Retain / rollbackKeep the saving while it remains real; recover when the envelope is crossed.
QUALIFICATION SPRINT
Start with the question your infrastructure budget actually depends on.
The first engagement answers one concrete question: can your accepted service run on fewer accelerators, lower power, a smaller provisioned system or a cheaper machine state—and if not, which physical bottleneck prevents it?
YOU PROVIDE
- Representative model or model family
- Production-like workload distribution
- Quality and service requirements
- Current machine / deployment constraint
- Power, rack or cost objective
LUMA RETURNS
- Reproducible baseline and service contract
- Candidate lower-resource configuration
- Physical deficit and intervention path
- Measured qualification evidence where available
- Deployment / design-in recommendation
For private AI, on-prem inference and infrastructure teams with stable, high-value workloads.Especially relevant where power, rack density, hardware count, data locality or predictable service economics matter.
Order a Qualification Sprint
WHERE LUMA EARNS ITS KEEP
Stable, expensive inference workloads with a reason to care about every watt and accelerator.
LUMA is designed for teams that already know the service they must deliver and want a defensible path to lower provision, power or cost without relaxing the accepted result.
Data locality, fixed capacity and predictable service economics make machine-state efficiency directly valuable.
Repeated production workloads where a small improvement in cards-per-service or J/output compounds across every hour of operation.
Sites where the binding constraint is power delivery, thermal headroom, rack density or accelerator count rather than model availability.
Teams deciding whether a workload justifies low-bit, memory-centric, FPGA or custom-accelerator intervention before paying the full NRE.
EVIDENCE STANDARD
Goodput, power and provenance travel together.
QUALITYSame accepted result
SERVICESame timed workload + SLO
RESOURCEMachine / accelerator count required
OUTPUTAccepted goodput / session density
ENERGYWhole-system joules / good output
LINEAGEExact release + machine identity
AUTHORITYPhysical evidence before deployment
Public and vendor data are useful priors for sizing and experiment design. They do not substitute for qualification of a customer release on its exact physical path.
WHAT YOU CAN BUY NOW
Three commercial paths, one economics-to-machine evidence chain.
Start at the decision boundary. LUMA deepens the intervention only as far as the measured customer value requires.
01Qualification SprintR1 requirement + binding deficit + Resource Boundary Report + qualified-state/deployment decision.Start order →
02Economic Control PilotLive qualified-state selection, apply/verify, savings telemetry and retain-or-rollback control.Start order →
03Hardware Design-InMeasured deficit translated into FPGA, accelerator, memory-side or semiconductor implementation and qualification.Start order →
04Qualified product pathPassing mechanisms become reusable machine states, deployment bundles and future appliance/IP/silicon products.See control logic →
DESIGN CUSTOMERS + TECHNICAL PARTNERS
We are assembling the physical evidence chain behind the product.
Design customers bring a real workload and service constraint. Technical partners bring a bounded implementation or measurement capability that plugs into a named input → artifact → evidence → downstream-consumer contract.