AWS Advanced Tier Partner
Claude Partner Network

AI, Engineered
for the Real World

Model training and optimization, GPU infrastructure, LLM migration, Data for AI.

Built by ex-AWS founders.

See Our Work

No pitch deck. You'll talk to an engineer on the first call.

What we do

Migration & Modernization
Off GCP, Azure, or on-prem onto AWS
GenAI in Production
Bedrock agents, RAG, fine-tuned models
GPU Infrastructure
Training and inference clusters at scale
Data & AI Platforms
Pipelines, lakehouse, ML operations
AI Security & Governance
Guardrails, audit trails, policy enforcement
Managed Services
We run what we build, on call

< Why Avashya >

Most AI projects
stall at the pilot.
Ours reach production.

Four things we do that agencies don't. Each one is why the last seven engagements shipped instead of ending in a slide deck.

Founder-Led Delivery

Three of the four founders are ex-AWS: GenAI, Data & AI, migrations, and platform engineering. They run the engagement, not just the sales call.

AWS Depth, Ten Accelerators

Advanced Tier Partner with specialist depth, plus ten tools we built: inventory assessment, dependency mapping, TCO modeling, LLM migration and evaluation, GPU optimization.

Benchmarked Before Cutover

Model swaps and migrations run side-by-side on your data first. One wearables platform moved off a third-party model provider with quality parity validated pre-cutover.

Single-Team Ownership

Strategy, build, cutover, and the managed run sit with one team. No handoff to an ops vendor that has never seen your architecture.

< Accelerators >

Ten tools we built
because we needed them

Five ship to you and keep running after we leave. Five run inside our delivery — you get the output, not the tool.

01 /

Ships to you

AIP

Avashya Intelligence Platform — Agent Observability & Evaluation

Agents in production drift, regress, and fail quietly. AIP watches them, scores them, and breaks them on purpose in a sandbox before your users do.

  • Per-user identity on every call, replacing shared API keys.
  • Automated nightly evaluations in place of manual review.
  • Disaster testing in sandbox before anything reaches production.
  • Full trace of inference traffic, cost, and per-user usage.

Running in a regulated fintech and a BFSI lender.

See the five we ship to you

< Case Studies >

Production outcomes. Measured, not modeled.

Seven engagements, named by sector under NDA.

Customer Success Story

Making a 1,056-GPU training cluster production-ready for a frontier AI lab

Read case study
All seven case studies

< Get in Touch >

Talk to an architect

Describe the workload you need to build, migrate, or optimize. A founder reviews it and replies with an architecture opinion.

1

We read your estate

Automated inventory scan of accounts, workloads, and dependencies. Usually two days, not two weeks.

2

You get a plan with numbers

Target architecture, TCO model, phase order, and the rollback path for each phase.

3

We build it and keep running it

Same engineers through cutover and into managed services.

Prefer to reach out directly?

hello@avashya.tech

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