Agents · Automation · Orchestration

AI opportunity identified.Potential unlocked.Execution — handled.

We turn AI ambition into working solutions across workflows, systems, and operations.

  • Austin
  • Hyderabad
  • Colombia
  • Peru
  • Nepal
  • Agent orchestration
  • Workflow automation
  • RAG & synthesis
  • MCP integrations
  • Evaluations
  • Legacy modernization
  • Cloud native
  • CI/CD
  • Infrastructure as code
  • Observability
  • Test automation
  • Performance engineering
  • Platform engineering
  • Release engineering
04Engineering disciplinesAI, product, DevOps, quality
03Engagement modelsExtension, dedicated, project
02OfficesAustin · Hyderabad, team across 5 countries
01Accountable teamOne lead, kickoff to release

Services

Four disciplines. One team.

AI work fails when the engineering around it is weak. We bring the whole set, so a model, the platform it runs on and the tests that keep it honest are never someone else’s problem.

Modern AI Engineering

Agent orchestration, multi agent systems, RAG, synthesis, MCP integrations, tool use, evaluations, and intelligent workflows.

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Product Engineering

Web and mobile applications, APIs, platforms, integrations, cloud native systems, and modernization.

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DevOps & Cloud

Cloud architecture, CI/CD, infrastructure as code, observability, platform engineering, reliability, and operations.

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Quality Engineering

Quality strategy, test automation, performance, integration testing, release engineering, and continuous quality.

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What changes

Modernization you can point at.

Most teams do not need another pilot. They need the work to move faster and the systems underneath it to stop getting in the way.

Work that runs itself

The handoffs, approvals and copy-paste between systems become one automated flow, with people kept in the loop where judgement is needed.

AI in production, not in a deck

Agents, retrieval and tool use built into the systems your team already runs — with evaluations proving they work before anyone depends on them.

Legacy systems that move again

Older platforms modernized incrementally, so the business keeps running while the architecture catches up.

How an AI modernization engagement runs

How an engagement runs

Narrow, proven, then widened.

Every phase ends in something you can judge. Nothing depends on a long build finishing before anyone sees whether it works.

  1. Map the work

    We follow the actual process, not the documented one, and come back with a shortlist of what is worth automating.

  2. Prove it on real data

    A narrow slice, measured against a test set built from real cases. If the numbers are not there, you know in weeks.

  3. Build the workflow

    The proven slice becomes a production path, integrated with your systems, with error handling and an audit trail.

  4. Harden it

    Evaluations in CI, tracing and cost controls, security reviewed, and somewhere for every failure mode to go.

  5. Run and extend

    We operate it and take on the next slice — or hand it over with the tests, runbooks and context to own it.

Engagement models

Start where it makes sense.

Team extension

Engineers where and when you need them.

Named engineers join your existing team, your standups and your board. You keep the roadmap and the process; we add the capacity and the skills you are short on.

Dedicated teams

A cross functional team on your roadmap.

A standing team — engineering, quality and DevOps together — working only on your product, with a lead who is accountable for what ships. It scales up and down as the roadmap changes.

Project delivery

Defined outcomes, engineering ownership from planning through production.

We take a defined outcome and own it end to end: planning, architecture, build, test and release. You get a scope, a schedule and one team answerable for both.


Global engineering. One accountable team.

A US contract and a US point of contact, backed by an engineering team across Colombia, Peru, Nepal and India — nearshore and offshore, so the working day keeps going. One team from kickoff to release, not a vendor you have to project-manage.

Contract
LeanTechOps LLC d/b/a OpsAway, a US entity
Delivery
The OpsAway team across Colombia, Peru, Nepal and India
Accountability
One lead answerable for what ships, start to finish
Overlap
Daily working hours that cross US business time
Tekgence
Ninjahire
KennelEyes
Cenor.ai

Clients

Teams we build for.

From production platforms to the products we build and run ourselves — the same team and the same accountability on every one.

Start a project

Questions

Before the first call.

How does an engagement start?
A call about the problem, then a short written proposal with a proposed team, a first milestone and a price. There is no discovery phase you have to pay for before you know what it costs.
Who owns what you build?
You do. Code, infrastructure, prompts, evaluation sets and documentation are yours, handed over in a state your own team can pick up and run.
How do the time zones work?
We agree a daily overlap with your business hours before the engagement starts, and the team works to it. Your point of contact is in the US.
Where is the team based?
Two offices: Austin, Texas and Hyderabad, India. Engineers in Colombia and Peru work with the Austin office, giving near-full overlap with US hours; engineers in Nepal work with the Hyderabad office. You contract in the US either way, and one lead stays accountable across both.
Who do we contract with?
LeanTechOps LLC d/b/a OpsAway — a US entity, under US law, invoicing in USD. Engineering is delivered by the OpsAway team across Colombia, Peru, Nepal and India.
How small can an engagement be?
Most start smaller than people expect: one problem, one team, one release. A narrow first slice is usually the fastest way to find out whether we work well together.
Do you only do AI work?
No. AI modernization is what we lead with, but it rarely stands alone — the product engineering, platform and quality work around it is usually what decides whether it survives contact with production.

Tell us what the work looks like today.

Send us the process you would most like to stop doing by hand. We will tell you honestly whether it is worth automating — and what it would take.