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NewAI engineering practice — assessment to production

We build the software that runs your business — and the AI that makes it faster

Beambyte Solutions is an engineering and consulting firm in Ahmedabad. Since 2015 we have designed, built and operated custom platforms for companies who need software shaped around their process — not the other way round. Today that work is increasingly AI-native, and we hold it to the same standard as everything else we ship.

Building software since
2015
Years in engineering delivery
10+
Core capability practices
6
Engineering base, serving globally
Ahmedabad

The stack we build on

Technologies we work with: TypeScript, Next.js, React, Python, Claude, PostgreSQL, AWS, Kubernetes, Terraform, .NET, React Native, GraphQL, Kafka, dbt, Snowflake, Docker, Go, pgvector, Azure, Odoo.

AI engineering

The gap between an AI demo and an AI system

A prototype convinces a room. A system has to hold up on a Tuesday afternoon when a user asks something the demo never covered, on data messier than the sample, at a cost the finance team already signed off on. That second thing is what we build.

  • From assessment to production

    A four-week readiness assessment identifies what is worth building. Everything after that is production engineering: evaluation suites, guardrails, cost ceilings and observability.

  • Deployed where your data allows

    Hosted frontier models with zero-retention terms, models inside your own cloud tenancy, or fully self-hosted open-weight models. The compliance requirement drives the choice.

  • Measured, not asserted

    Accuracy against a golden set, latency at the ninety-fifth percentile, cost per transaction. Every release is scored before it ships, and the suite is yours to re-run.

How we work

A delivery process with no surprises in it

The same shape whether the engagement is a four-week assessment or an eighteen-month platform build. You always know which phase you are in and what comes out of it.

  1. 011–2 weeks

    Understand

    We start with the business outcome, not the feature list. Interviews with the people who will use the system, a look at the data and integrations that already exist, and an honest read on what is actually constraining you today.

    • Problem statement
    • Constraint and risk register
    • Success measures
  2. 022–4 weeks

    Shape

    Architecture, interface design and a scoped backlog. Where there is genuine technical uncertainty we build a throwaway spike against real data to resolve it before it becomes an estimate you have to trust.

    • Target architecture
    • Interactive prototype
    • Range-based estimate
  3. 03Continuous

    Build

    Two-week increments, each ending in working software deployed to an environment you can use. Your repository, your cloud account, tests and CI from the first commit rather than retrofitted before handover.

    • Deployed increments
    • Automated test suite
    • Sprint demos
  4. 041–3 weeks

    Harden

    Load and security testing, accessibility verification, observability wired up, runbooks written and a rollback path proven. The work that determines whether launch week is uneventful.

    • Performance baseline
    • Security review
    • Operational runbook
  5. 05Per release

    Launch

    Progressive rollout with monitoring against defined service objectives, so problems are caught by instrumentation rather than by your customers, and a rollback is a routing decision.

    • Release plan
    • Monitoring dashboards
    • Go-live support
  6. 06Ongoing

    Evolve

    Support under defined SLAs, dependency and security patching, and a roadmap that keeps moving. Or a structured handover to your own team, which is a perfectly good outcome.

    • Support SLA
    • Roadmap reviews
    • Knowledge transfer

Where we work

Domains we have gone deep enough in to be useful on day one

Not a list of every sector we would accept work from — these are the ones where we already understand the workflows, the constraints and the regulation.

How we operate

Six commitments we hold ourselves to

These are the things clients tell us made the difference — usually in contrast to a previous engagement somewhere else.

More about the firm
  • Say what will not work

    The most valuable thing a technology partner can do is talk you out of the expensive mistake. If AI is the wrong tool, if the platform you have chosen is wrong for your catalogue, if the timeline cannot hold — you hear it while it is still cheap to change.

  • You own everything

    Your repository, your cloud account, your data, your IP. No proprietary framework you have to keep paying to maintain, and no hostage-taking at the point of handover.

  • Working software over status reports

    Progress is demonstrated in a deployed environment you can click through, every two weeks. A green project status with nothing to show is not progress.

  • Measure before claiming

    Accuracy, latency, cost per transaction, conversion — instrumented and reported from real usage. Especially for AI features, where the demo and the deployment behave very differently.

  • Build for the team who inherits it

    Typed, tested, documented, with architecture decisions recorded and the reasoning preserved. The measure is whether an engineer who joins next year can make a change safely.

  • Security is not a phase

    Threat modelling in design, scanning in the pipeline, least privilege by default, and secrets managed properly from the first environment rather than the one before launch.

Questions

Before you get in touch

What size of engagement do you take on?

Most engagements start somewhere between a four-week assessment and a six-month build with a small dedicated team. We are candid when something is too small to justify the overhead of an external partner, or large enough that you would be better served building the capability in-house — and in the second case we will help you do that.

How do you handle time zones and communication?

Our team is based in Ahmedabad and works with clients across India, the Gulf, Europe, the UK and North America. We commit to a defined overlap window with your working day, run written-first communication so decisions are searchable, and hold a fixed weekly review regardless of geography.

What happens to our data during a project?

Access is least-privilege and time-bound, production data is not copied to developer machines, and anonymised or synthetic data is used for development wherever the work permits. Data handling terms including residency, retention and sub-processors are set out in the contract before any access is granted.

Can you take over a project someone else started?

Yes, and it is a large share of what we do. We begin with a short assessment of the codebase and infrastructure so both sides know what is actually there, then agree a stabilisation plan before adding new features on top of it.

Do you work with startups as well as established companies?

Both, though the engagement shape differs. Early-stage work is usually a small team optimising for speed of learning; established companies more often need integration with existing systems, migration planning and a compliance posture. We are explicit about which mode a project is in, because the trade-offs are genuinely different.

How do you price AI work when usage is unpredictable?

Engineering effort is priced like any other build. Model and infrastructure costs are passed through at cost with a modelled forecast produced during the assessment, plus hard budget limits and per-feature telemetry so spend never arrives as a surprise.

Tell us what you are trying to build

Send a short description of the problem. You will get a reply from an engineer, not a sales sequence — usually with a first read on the approach and whether we are the right partner for it.

Or email us directly at info@beambytes.com