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QSI is a fail-open inference optimization layer that improves throughput and power efficiency without touching GPUs, drivers, or models.
Infrastructure software that lets data centers sell more AI per megawatt
Infrastructure software that lets data centers sell more AI per megawatt
Non-Intrusive Integration
/
Fail-Open Safety
/
Throughput per Watt
Fail-open inference optimization.
If it doesn’t improve performance, it steps aside automatically.
BOUNDED LATENCY
Predictable latency. Protected SLAs. Hard timeouts and enforced fallback guarantee bounded response times and uninterrupted service.
LOW-POWER TARGET
More AI per rack. Less power per token. QSI reduces power and cooling pressure without increasing rack complexity.
INFRASTRUCTURE-FIRST DESIGN
QSI integrates as a sidecar alongside existing inference stacks to reduce inference runtime overhead and energy per token — while preserving deterministic host execution, strict SLAs, and operational safety.
Non-intrusive
/
Fail-open
/
Baseline vs After
FAIL-OPEN DESIGN
Zero operational risk. If QSI times out, fails, or is removed, inference instantly reverts to the standard host path. Worst case: performance is unchanged. No single point of failure.
FAIL-OPEN DESIGN
Zero operational risk. If QSI times out, fails, or is removed, inference instantly reverts to the standard host path.
Worst case: performance is unchanged. No single point of failure.
FAIL-OPEN DESIGN
Zero operational risk. If QSI times out, fails, or is removed, inference instantly reverts to the standard host path.
Worst case: performance is unchanged. No single point of failure.
LOW-POWER TARGET
More AI per rack. Less power per token. QSI reduces power and cooling pressure without increasing rack complexity.
BOUNDED LATENCY
Predictable latency. Protected SLAs. Hard timeouts and enforced fallback guarantee bounded response times and uninterrupted service.
(Q3)
Pilot Integration
Controlled deployment with a pilot partner via staged rollout (shadow → canary → ramp). Instant rollback, observability, and no-downtime safeguards.
(Q1)
System Readiness
Define the operational contract: fail-open behavior, bounded latency, and rollback guarantees. Establish baseline measurement suite for production inference stacks.
(Q2
Baseline vs After Validation
Validate throughput-per-watt and SLA/tail-latency improvements using a standardized “Baseline vs After” methodology in controlled evaluation environments.
(Q4)
Production Scaling
Production hardening and scale-out readiness: monitoring, runbooks, security posture, and partner onboarding for multi-rack deployments.
REQUEST ACCESS
REQUEST ACCESS
request@qsi.tech
Terms of Use
© 2026 QSI. All rights reserved.
Targets validated via baseline vs after.
Privacy Policy
contact us
QSI is a fail-open inference optimization layer that improves throughput and power efficiency without touching GPUs, drivers, or models.
Infrastructure software that lets data centers sell more AI per megawatt
Fail-open inference optimization.
If it doesn’t improve performance, it steps aside automatically.
Non-Intrusive Integration
/
Fail-Open Safety
/
Throughput per Watt
FAIL-OPEN DESIGN
Optional acceleration. On fault or timeout, execution instantly reverts to the standard host path. No single point of failure
LOW-POWER TARGET
Designed for high-density racks with a minimal thermal footprint. More AI per rack. Less power per token
BOUNDED LATENCY
Hard timeouts and enforced fallback protect SLAs and preserve service continuity
INFRASTRUCTURE-FIRST DESIGN
We build fail-open sidecar integrations for production inference.
Our software reduces inference runtime overhead while preserving deterministic host execution, strict operational safety boundaries, and baseline-measurable behavior.
(Q3)
Pilot Integration
Controlled deployment with a pilot partner via staged rollout (shadow → canary → ramp). Instant rollback, observability, and no-downtime safeguards.
(Q1)
System Readiness
Define the operational contract: fail-open behavior, bounded latency, and rollback guarantees. Establish baseline measurement suite for production inference stacks.
(Q2
Baseline vs After Validation
Validate throughput-per-watt and SLA/tail-latency improvements using a standardized “Baseline vs After” methodology in controlled evaluation environments.
(Q4)
Production Scaling
Production hardening and scale-out readiness: monitoring, runbooks, security posture, and partner onboarding for multi-rack deployments.
Terms of Use
Privacy Policy
© 2026 QSI. All rights reserved.
request@qsi.tech
REQUEST ACCESS
Fail-open inference optimization.
If it doesn’t improve performance, it steps aside automatically.
Request Access
QSI is a fail-open inference optimization layer that improves throughput and power efficiency without touching GPUs, drivers, or models.
Infrastructure software that lets data centers sell more AI per megawatt
Non-Intrusive Integration
/
Fail-Open Safety
/
Throughput per Watt
INFRASTRUCTURE-FIRST DESIGN
QSI integrates as a sidecar alongside existing inference stacks to reduce inference runtime overhead and energy per token — while preserving deterministic host execution, strict SLAs, and operational safety.
Non-intrusive
/
Fail-open
/
Baseline vs After
FAIL-OPEN DESIGN
Zero operational risk. If QSI times out, fails, or is removed, inference instantly reverts to the standard host path.
Worst case: performance is unchanged. No single point of failure.
LOW-POWER TARGET
More AI per rack. Less power per token. QSI reduces power and cooling pressure without increasing rack complexity.
BOUNDED LATENCY
Predictable latency. Protected SLAs. Hard timeouts and enforced fallback guarantee bounded response times and uninterrupted service.
(Q2
Baseline vs After Validation
Validate throughput-per-watt and SLA/tail-latency improvements using a standardized “Baseline vs After” methodology in controlled evaluation environments.
(Q1)
System Readiness
Define the operational contract: fail-open behavior, bounded latency, and rollback guarantees. Establish baseline measurement suite for production inference stacks.
(Q3)
Pilot Integration
Controlled deployment with a pilot partner via staged rollout (shadow → canary → ramp). Instant rollback, observability, and no-downtime safeguards.
(Q4)
Production Scaling
Production hardening and scale-out readiness: monitoring, runbooks, security posture, and partner onboarding for multi-rack deployments.
[3]
Roadmap
REQUEST ACCESS
request@qsi.tech
Terms of Use
© 2026 QSI. All rights reserved.
Targets validated via baseline vs after.
Privacy Policy