# Where the systems go to work

How our schedulers, brokers and telemetry are deployed in real operations, from GPU fleet optimization and agentless observability to governed autonomous AI agents.

Cloud Infrastructure & High-Scale Tech

## [Fleet Observability & Infrastructure Simplification](https://kushawaha.com/solutions/enterprise-infra-modernization)

#### The challenge

Engineering teams often run multiple conflicting monitoring agents across thousands of servers, resulting in memory overhead, version drift, and slow incident triage.

#### Our approach

We replace bulky client daemons with agentless SSH probes that gather full kernel and GPU counters in one second, paired with automated root-cause analysis runbooks.

#### Outcomes

Zero monitoring daemons installed on production targets

Unified GPU and CPU telemetry across mixed bare-metal and cloud servers

Over 75% reduction in manual troubleshooting time during system outages

Built on

Autonomous SRE & Telemetry Distributed GPU Compute

[Request Technical Brief](https://kushawaha.com/contact)

Enterprise Software & Regulated Services

## [Governed AI Agent Execution & Spend Controls](https://kushawaha.com/solutions/safe-ai-deployment)

#### The challenge

Unrestricted autonomous AI agents can leak root API tokens, trigger unbounded inference loops, and generate unexpected cloud bills within hours.

#### Our approach

We put an in-app proxy between agents and model APIs to strip root credentials, inject Ed25519-signed session tokens, and return HTTP 429 when monthly dollar ceilings are reached.

#### Outcomes

Complete protection against master provider API token theft

Guaranteed monthly expenditure ceilings per application sandbox

Dynamic fallback to local offline model servers during provider outages

Built on

Autonomous AI Runtimes Zero-Trust Gateways

[Request Technical Brief](https://kushawaha.com/contact)

High-Performance Computing & Machine Learning

## [Heterogeneous GPU Cluster Scheduling](https://kushawaha.com/solutions/distributed-gpu-management)

#### The challenge

Most cluster tools only support one GPU brand, leaving AMD, Apple Silicon, and Intel hardware idle while teams wait for expensive cloud instances.

#### Our approach

We deploy a single-binary gossip scheduler that discovers and balances tasks across mixed NVIDIA CUDA, AMD ROCm, Apple Metal, and Intel Arc hardware without a central master node.

#### Outcomes

40% to 60% reduction in cluster idle time across mixed hardware fleets

Single-binary deployment under 25 MB with zero runtime dependencies

Resilient peer-to-peer cluster coordination with zero single points of failure

Built on

Distributed GPU Compute

[Request Technical Brief](https://kushawaha.com/contact)

Staffing, Logistics & Field Operations

## [Offline-First Field Platforms & Labor Scheduling](https://kushawaha.com/solutions/resilient-workforce-operations)

#### The challenge

Field teams working in remote or low-connectivity zones frequently lose submission data, while dispatchers struggle to cover last-minute shift shortages.

#### Our approach

We build offline-first web apps that store records in local IndexedDB outboxes and sync automatically when reconnected, paired with an automated shortage forecasting engine.

#### Outcomes

Uninterrupted field check-ins and deployment tracking without cell signal

Portable worker records that function across independent business accounts

Automated shift shortage detection that alerts dispatchers hours before shift starts

Built on

Enterprise Applications Zero-Trust Gateways

[Request Technical Brief](https://kushawaha.com/contact)

## Have a custom distributed systems challenge?

Our principal architects partner with enterprise technical leaders to design and implement tailored, zero-trust infrastructure.

[Initiate Solution Discussion](https://kushawaha.com/contact) [Explore Capabilities](https://kushawaha.com/capabilities)

---

Source: https://kushawaha.com/solutions
Published by Kushawaha Group. Index of all pages: https://kushawaha.com/llms.txt