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AI Consulting Services

Before you build, find out if AI is even the right tool.

An honest, technical assessment of where AI can move the needle in your business, and where it can't. We scope feasibility, cost, and risk before a single line of production code, so the build that follows is the right one.

Same vetting bar either way, whether we staff the project or fill the seat. See the rubric

Documents flowing into a processor and out as answers in a chat interface
Feasibility

A clear-eyed read on whether AI clears the bar over your current process.

Data audit

What you actually have, and what's missing to make AI work.

Build vs. buy

When an off-the-shelf tool beats a custom build, we say so.

Roadmap

A phased plan with cost and risk attached to each phase.

What we build

What an engagement actually covers.

We audit your processes and data to find where AI has real leverage, and where the honest answer is that it doesn't, yet.

Process auditData readinessROI modelingRisk assessment
See consulting work

A hands-on spike against your real data to validate an approach before it becomes a funded project, so the go/no-go decision is based on evidence.

PrototypingData validationModel evaluation
See feasibility work

An honest comparison of building custom versus buying an existing tool, without a vendor kickback distorting the recommendation.

Vendor evaluationCost modelingIntegration scope
See strategy work

A phased plan, with a real cost and timeline estimate per phase. That a build team (ours or yours) can execute against.

Phased roadmapCost estimationTeam scoping
See roadmap work
What we build with

Current tools, not last year's.

Assessment
Data auditsROI modelingTechnical spikes
Models
ClaudeGPTOpen models
Infra
AWSGCPOn-prem review
Proof

Shipped, not slideware.

Agentic support layer
AI Agents

Agentic support layer

A feasibility spike and eval harness built before a single line of the production agent was written.

PythonRAGLangChain
Read the case study
What clients say

On camera, in their own words.

Client video

Why he brought his development work to Code Elevator.

MikePlays here
How we run it

Scoped fast. Shipped on a real timeline.

011 weekDiscoveryInterviews with your team and a review of the data and systems in play, to understand the problem precisely.
021–2 weeksFeasibility spikeA small, hands-on technical test against your real data to see if the approach actually works.
031 weekRecommendation and roadmapA written report: go or no-go, and if go, a phased roadmap with cost and risk attached.
04OngoingOptional build handoffIf you proceed, the same team that scoped it can build it, no re-explaining the problem to a new set of engineers.
Related services

Building something adjacent?

Questions

Answered before you ask.

We tell you. A feasibility assessment that always concludes 'yes, build it' isn't a real assessment, sometimes the honest recommendation is a simpler rules-based system, or nothing at all.

No. The roadmap is written to be executable by any team. Plenty of clients use it to brief an internal team or a different vendor.

Most engagements run two to four weeks from kickoff to a written recommendation, depending on how much data review and stakeholder interviewing is needed.

No. We're not paid by any model or platform vendor, so the build-vs-buy recommendation is based on fit for your case, not a partnership incentive.

What you're not risking

Every way out of this build is already written down.

You own it, from day one

Code, prompts, models and pipelines: all work-product IP assigns to you by contract from day one, not on final payment.

No vendor lock-in

Nothing is locked to us or to a proprietary platform you can't leave. You get the repository, the documentation, and full access.

Get started

Bring us the question. We'll tell you what's realistic.

"Should we build this with AI" is a real question with a real answer. We'll help you find it before you spend the budget.

We reply within an hour during our working day in India and the UAE.

Chat with our team