AI ENGINEERING
AI consulting services that end in working software
Our AI consulting services take you from a promising idea to a production system on your own data. Agents, RAG pipelines, copilots and generative AI, built by one team and signed off gate by gate.
AI Jumpstart
- Ranked list of AI use cases with effort and risk
- Working prototype on a sample of your data
- Eval report with a go, reshape or stop recommendation
OVERVIEW
Enterprise AI solutions that hold up after launch
Most AI pilots stall between the demo and the first real user. We design for that gap from day one, with evaluation sets, permission checks, cost limits and monitoring built in. You see evidence at every gate and you own everything we produce.
SERVICES IN THIS PRACTICE
What our AI consulting services cover
AI Agents
Agents that plan steps, call your systems through approved tools and hand work to a person when confidence drops or rules require it.
Explore AI AgentsRAG Systems
Retrieval pipelines that answer from your documents with citations, permission filters and an evaluation suite that runs before every release.
Explore RAG SystemsGenerative AI
Drafting, summarising, extraction and classification built into the workflows your teams already use, with review steps where accuracy matters.
Explore Generative AIAI Copilots
Internal assistants that answer from company knowledge, respect each user's access rights and show the source behind every answer.
Explore AI CopilotsAI MVP and PoC
A working prototype on your real data in two weeks, with an eval report and a clear go, reshape or stop decision.
Explore AI MVP and PoCLLM evaluation and monitoring
Test sets, regression checks, cost tracking and drift alerts, so you know how the system behaves once real users arrive.
USE CASES
Where AI earns its place
Contract review for law firms
Associates get clause extraction and risk flags across hundreds of contracts, with every finding linked to the exact page it came from.
Support ticket triage
An agent reads incoming tickets, pulls account history from your CRM, drafts a reply and routes edge cases to the right specialist.
Audit evidence gathering
A CA practice collects invoices, ledgers and emails into one queryable layer, so audit teams spend less time chasing documents.
Engineering knowledge search
Your engineers ask questions across wikis, tickets and design docs, and get cited answers filtered by the projects they can access.
HOW WE DELIVER
Five gates. You sign each one.
Every AI Engineering engagement runs on PRISM OS. Nothing moves to the next phase until you approve the evidence.
Plan
Pick one use case, its owner and success measures
You sign: Problem BriefResearch
Audit data sources, access rules and failure risks
You sign: Frozen PRD-LiteImplement
Build a prototype on your data with an eval set
You sign: Working prototype + eval reportStabilise
Harden security, latency, cost and fallbacks before launch
You sign: 3-click UAT sign-offMaintain
Monitor quality and drift, tune prompts and retrieval monthly
You sign: IP handover + warrantyAI Jumpstart
A fixed-scope first step. You keep everything it produces, whether or not you build with us.
- Ranked list of AI use cases with effort and risk
- Working prototype on a sample of your data
- Eval report with a go, reshape or stop recommendation
WHY SMARTX
Why SmartX for AI Engineering
Evals before demos
We build the test set first, so every prompt or model change is measured against the questions your users actually ask.
Prototype team ships production
The engineers who build your prototype lead the production build. No hand-off to a separate team and no context lost between phases.
Trusted on voice and AI
blueShepherd GmbH has worked with us on cloud, voice assistant and AI projects, and its founder credits us with keeping to time and cost.
You own every artefact
Code, prompts, evaluation sets, decision records and datasets belong to you from the first commit, ready for your team to run.
TOOLS WE USE
The stack, chosen per problem
ENGAGEMENT MODELS
Choose how we work together
Every model keeps the same signed gates, fixed milestones and full code ownership.
Gated delivery pod
A senior pod owns the outcome from Problem Brief to production, priced per gate so you can stop at any signature.
Dedicated engineers
Engineers who join your team and sprints, with PRISM briefs and evidence reviews added on top of your process.
PRISM OPS retainer
Hosting, security and a monthly improvement budget, run by the same engineers who built the system.
SELECTED WORK
Evidence, not promises.
From idea to post-PMF growth for an EdTech startup
WeXL went through the Startup Factory stages, from idea validation and MVP to product-market fit and go-to-market.
An EdTech company, now in its post-PMF growth phase.
Read the case study“SmartX Startup Factory helped us get our ideas to market faster. Their team is very adaptive and understands lean startups. They tweaked the process to suit our business and helped in product delivery.”
FAQ
Questions before you book
Not covered here? Ask on the call.
What does an AI engagement with SmartX include?
Every engagement runs on PRISM OS. A paid Discovery Sprint or AI Jumpstart defines the problem, a two-week prototype proves it on your data, and a 4–12 week build takes it live with monitoring, IP handover and a warranty.
Are you an LLM development company or a consultancy?
Both. We advise on where AI fits, then our engineers build it. That includes custom LLM development where fine-tuning genuinely helps, though most use cases get better results from retrieval, tools and careful prompting on existing models.
Which models do you use?
We work with OpenAI, Anthropic, Google and open-weight models such as Llama and Mistral. We choose per task based on accuracy against your eval set, latency, running cost and where your data is allowed to go.
Can AI work with data spread across CRMs, ERPs and email?
Yes. We often start by building a governed query layer over those sources, with access rules and audit logs. Agents and copilots then answer from current records instead of stale exports or copied spreadsheets.
Do you work with businesses outside IT?
Yes. Law firms, CA and audit practices, manufacturers and startups all bring AI problems to us. The process stays the same: a signed problem brief, a prototype on your data, then a measured production build.
START WITH CLARITY
Find the AI use case worth building first
Book a free discovery call and spend 30 minutes with an engineer on your data, your constraints and your first realistic win.
- 1We review your context within one business day.
- 2A senior product engineer joins the call.
- 3You leave with a clear recommended next step.