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BlueOrbitAI
Enterprise AI Consultancy

Know which AI projects are worth starting, before you start them.

Most enterprise AI budget is spent on pilots that never reach production. We assess your data, your systems and the work your people actually do, then tell you which use cases will pay for themselves, in what order, at what cost, and which ones to leave alone.
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What’s included

  • Readiness assessment
  • Use case roadmap
  • Architecture review
  • Governance

2 wks

from the first call to a costed, sequenced roadmap

Yours

every document we produce, whoever builds it afterwards

Capabilities

What we deliver

An independent read on where AI will actually pay for itself in your organisation, delivered as a costed, sequenced roadmap your board can approve or decline on the evidence.

  • AI readiness assessment

    An honest read on your data, systems, security posture and team, and what each one has to change before an AI project can succeed.

  • Use case discovery and scoring

    Workshops with the people doing the work, then every candidate scored on value, feasibility and risk, so the running order is argued rather than assumed.

  • Architecture and build-or-buy review

    Whether to buy a product, extend a platform you already pay for, or build something of your own. We say buy whenever buying wins.

  • Governance and risk framework

    Approval gates, human oversight, model and data policies, and an audit trail your risk committee can actually read.

  • Proof of value design

    A pilot with a success threshold and a stop condition agreed before it starts, so it ends in a decision rather than another demo.

  • Team enablement

    Workshops and written standards so your own engineers can carry the work, instead of depending on an agency forever.

Why it works

Advice from people who ship.

We are an engineering studio first. Every recommendation here comes from building and operating these systems in production, not from a slide library.

Technologies we use

  • OpenAI
  • Anthropic
  • Google Gemini
  • Azure AI Foundry
  • AWS Bedrock
  • Open-weight models
  • LangGraph
  • Model Context Protocol
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  1. A roadmap with prices on it

    Each use case carries a cost estimate, an effort band and a payback case, so the decision in front of your board is a business one.

  2. Risks named early, in writing

    Data gaps, integration blockers, regulatory exposure and the things that simply will not work. Named in the first fortnight, not discovered in the sixth month.

  3. No obligation to build with us

    The assessment stands on its own and is written so your in-house team or another supplier can act on it.

  4. The recommendation that fits

    Including buying a product rather than building one, and including not running the project at all. A rules engine is often cheaper, faster and more predictable than a model.

How a consultancy engagement runs

  1. 01

    Frame

    We agree the question the engagement has to answer, and what a useful answer looks like.

  2. 02

    Assess

    Interviews with the people doing the work, a read of your systems and data, and a security and compliance check.

  3. 03

    Prioritise

    Every candidate use case scored on value, feasibility and risk, then sequenced into a plan.

  4. 04

    Report

    A costed roadmap, an architecture recommendation and the risks, presented to your team and your board.

  5. 05

    Decide

    You choose what happens next. If you want it built, the roadmap becomes the statement of work.

Related case studies

All case studies

Enterprise AI consultancy: common questions

Straight answers to what we are asked most often.

A written assessment, a scored and sequenced use case roadmap with cost and effort bands, an architecture and build-or-buy recommendation, and a risk and governance section. It is yours to keep and to share with anyone.

No. The assessment is priced and delivered on its own, and it is written so another team can act on it. If you do want us to build, the roadmap becomes the basis of the statement of work.

Two weeks for a focused question, such as one department or one process. Four to six weeks where the scope covers several business units or a regulated environment.

Where that is the answer, yes. A rules engine, a fixed integration or a change to the process itself is often cheaper, faster and more predictable, and we would rather say so than sell you a model.

Yes, and we prefer it. Most engagements run with your own engineers and process owners in the room, which is also the fastest way for the knowledge to stay with you.

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