Made difficult by fragmented telemetry
Fragmented tooling across hardware, firmware and orchestration layers means problems surface only after customer impact.
Your AI Infrastructure engineer
AI-powered
Infra observability & remediation
Built for enterprise infrastructure and ops teams
Asama AI watches over your entire stack — GPU, compute, network, and storage — across on-prem, data center, and private cloud infrastructure.
Specialised AI Agents surface hardware faults, configuration drift, CVEs, and anomalies before they become incidents. Agentic workflows remediate them, with humans in the loop.
Remediation First
Agentic Workflows
SOC 2 Type II
Seamlessly works with leading Infrastructure providers
The Problem
Infrastructure engineers have gotten used to this
Three compounding failure modes — each normalized, each costing real engineering time every single day.
Stuck with scripts & automations
Recovery lives in wikis and tribal knowledge. Scripts break on every new SKU or firmware upgrade — and maintaining them is a full-time job.
Ignored until compliance flags it
CVEs across BMC, OS and kernel accumulate unpatched. Cross-team coordination to schedule maintenance windows adds weeks of exposure time.
40%
of the team's daily bandwidth consumed by reactive debugging & not resolving the root cause.
Gaps
- Broken Telemetry
- Manual Diagnosis & RCA
5–15%
of inventory stuck in the maintenance queue at any given time due to manual interventions.
Gaps
- Tribal Knowledge
- Stale Runbooks
90%
of live CVEs remain unmitigated fleet wide - waiting for upgrade & maintenance.
Gaps
- Exposure Window
- Compliance
Introducing Asama AI
Your infra team should spend time on outcomes, not incidents.
Asama AI is the AI infrastructure engineer for GPU, compute, network, and storage — across on-prem, data center, and private cloud. Asama AI turns raw telemetry into detection, remediation and security intelligence.
See how it works DETECT
Know before your customers do.
Asama AI continuously scores telemetry across hardware platforms & components, GPU, OS, Kernel, firmware and VM & Orchestrator - surfacing config drifts, performance anomalies, and hardware faults under 5 minutes, not 4 hours.
< 5 min mean time to detect
REMEDIATE
Fix it once. Never manually again.
AI Root Cause Analysis examines firmware deltas, config changes, SKU mismatches, telemetry gaps, and log evidence, then surfaces a ranked, evidence-backed conclusion with recommended next steps for remediation.
80%+ reduction in manual triage time
SECURE
CVEs closed before the audit finds them.
Asama AI prioritizes vulnerability by your environment's OS, BMC and firmware stack - and coordinates patching windows across the team without manual chasing.
90% CVEs unmitigated today — fixable with Asama AI
The Full Stack
Four layers. Zero Silent Failures.
When infrastructure feels "flaky," the root cause is trapped in the cracks between teams and tools. We unify your entire infrastructure stack into a single reasoning layer, catching and fixing silent performance degradation before it hits your applications.
01
Hardware Platform
Asama AI monitors your entire hardware stack — compute, storage, GPU servers, NICs, switches, routers, firewalls, PSUs, and every server sub-component including memory, processors, GPUs, disks, and motherboards. Faults are detected continuously. Anomalies are detected by benchmarking each device against its peers in your fleet, not generic thresholds.
02
Firmware
Asama AI tracks firmware state across every server, SSD, and physical device in your fleet — flagging drift, surfacing CVEs, and enforcing golden baselines. When something fails, it figures out the root cause and handles the upgrade with human advice.
03
OS, System Packages & Services
Kernel panics. Silent service crashes. Package drift between nodes. Post-patch regressions. These are the failures that take your best engineers hours to diagnose. Asama AI detects them continuously, traces root cause to the exact package version, kernel state, or service conflict, and handles remediation — rollbacks, patches, service recovery — with your approval at every step.
04
VM & Orchestrator
Misconfigured limits, orphaned VMs, configuration drift, and stale reservations silently drain capacity and destabilise clusters. Asama AI detects them continuously and fixes them, sequenced safely around live workloads.
01 — Hardware Platform
Chassis Riser Batch Degradation
32 nodes showed intermittent memory-bandwidth drops over 11 days. Utilization dashboards stayed green. No hard failures were logged.
6 nodes remediated. Zero customer-facing incidents. Mean time from signal to ticket: 4 minutes.
How Asama AI reasoned through it
- 1
Peer-relative benchmark
P95 latency outliers isolated to a cluster of 8 nodes sharing a common deployment window.
- 2
Asset manifest cross-correlation
Batch of PCIe riser cards deployed 90 days prior matches all affected nodes.
- 3
Targeted validation burn-in
6 nodes with matching riser SKU isolated and stress-tested against fleet baseline.
- 4
Automated remediation ticket
Swap order raised and scheduled before any workload degradation reached applications.
02 — Firmware
PCIe Link Downgrade — Silent Throughput Loss
An AI inference cluster reported GPU utilization at 72% — within normal range. Actual workload throughput had quietly dropped 31% over 8 days.
Full Gen4 x16 restored across all 4 GPUs. Throughput recovered in 22 minutes. No training jobs interrupted.
How Asama AI reasoned through it
- 1
Utilization-vs-throughput divergence
Asama AI flags that utilization/throughput ratio has drifted 31% below fleet baseline over 8 days.
- 2
PCIe link state audit
4 GPUs found operating at Gen3 x8 instead of Gen4 x16 — half the theoretical bandwidth.
- 3
Root cause trace
Recent BIOS update reset PCIe slot negotiation policy fleet-wide on affected SKU.
- 4
Sequenced rollback & validation
Nodes drained, BIOS rollback applied, throughput validated against baseline before reintroduction.
03 — OS, System Packages & Services
Kernel Panic Cascade from Mixed C-State Policy
Sporadic kernel oops in dmesg, no discernible pattern. Three separate SRE escalations over two weeks — each resolved individually, root cause unknown.
Zero kernel oops in 30 days post-remediation. SRE escalation queue cleared.
How Asama AI reasoned through it
- 1
dmesg log correlation
NMI watchdog timeout events surface across 8 nodes — sparse individually, significant in aggregate.
- 2
BIOS config cross-reference
C-state power management settings found inconsistent across fleet — mixed between OS-controlled and firmware-controlled.
- 3
Kernel version mapping
Affected nodes traced to a known upstream C-state regression introduced in a patch 6 weeks prior.
- 4
Uniform policy enforcement
Fleet-wide C-state standardization applied and validated over a 24-hour stability burn window.
04 — VM & Orchestrator
Safe Node Drain During Active Distributed Training
A GPU node failing a health probe needed remediation mid-run on a 72-hour distributed training job. Traditional drain would have collapsed the gradient sync ring.
72-hour training job completed uninterrupted. Full remediation cycle took 8 minutes.
How Asama AI reasoned through it
- 1
Topology graph analysis
Failing node's role in the training ring identified — rank 7 of 16, critical to gradient sync topology.
- 2
Safe drain sequence calculation
Cordon + workload migration path calculated to preserve ring topology without checkpointing the job.
- 3
Orchestrated remediation
Cordon → migrate → drain → fix → validate → uncordon executed as a single automated workflow.
- 4
Synthetic validation
Synthetic workload run on repaired node before reintroduction to confirm GPU health against baseline.
The Full-Stack Network Effect:
Your infrastructure telemetry and tools says healthy. Your application team says otherwise. Real resolution only happens when hardware telemetry, OS signals, firmware state, and your orchestration layer share a single view. That is full-stack remediation.
Why Teams Switch
You Have Monitoring. But Do You Have Resolution?
Existing monitoring tools tell you when a system breaks. Asama AI bridges the critical operational gap between automated detection and actual, targeted remediation. We don't replace your current stack or custom scripts; we turn their passive alerts into automated, actionable intelligence.
The Current State vs. The Asama AI Advantage
The Operational Risk (Your Current Stack)
The Strategic Solution (With Asama AI)
Manual, Time-Intensive Diagnosis
Alerts trigger instantly, but isolating the underlying issue remains a manual engineering bottleneck.
Unified Full-Stack Telemetry
Instantly correlates signals across hardware, firmware, OS, and virtualization into a single structured timeline.
High Dependency on Senior Personnel
Interpreting complex multi-layer alerts requires your most expensive and constrained engineering talent.
Democratized Infrastructure Intelligence
Synthesizes complex environmental data, providing clear, high-confidence context to operational teams.
The Deep-Infrastructure Blind Spot
Zero visibility below the OS layer, leaving critical hardware and firmware faults entirely undetected.
Sub-OS Deep Visibility
Continuous health mapping across bare-metal, firmware, and hypervisor levels to eliminate invisible blind spots.
Operational Inertia & Delayed Response
Standard alerts simply create a ticket, adding to the backlog while waiting for manual triage.
Dynamic, Adaptive Remediation
Generates context-specific remediation blueprints designed to fit the exact hardware and software footprint without breaking.
Severe Institutional Knowledge Drain
When a senior engineer leaves the organization, critical system context and troubleshooting expertise walk out the door.
Compounding Institutional Memory
Captures and digitizes every incident and environment response, ensuring systemic intelligence stays inside your organization.
Seamlessly works with leading Infrastructure providers
What engineering leaders say
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Stop being paged at 3am
Join enterprise teams like yours who've handed routine remediation to Asama AI and reclaimed their on-call schedules.