:: AI services / AI consulting
AI consulting services that end in something that works
Most AI consulting ends with a slide deck. Ours ends with a ranked list of use cases, a costed plan and, where it makes sense, a working proof of concept on your own data. The people who advise you are the engineers who would build it.
Readiness assessment in 2 to 3 weeks
Proof of concept on your data
Generative AI and classic ML
:: What we do
What our AI consulting covers
Pick one part or run them in order. Each one produces something you keep, even if you never hire us to build.
01
AI readiness assessment
We look at your data, systems, team and processes and tell you plainly what AI can and can’t do for you today. You get a short report and a list of gaps to close first.
02
AI strategy and roadmap
We map your processes, score each AI idea by value, effort and risk, and turn the best three into a 6 to 12 month plan with budgets and owners.
03
Use-case discovery workshops
Half-day sessions with your sales, service or operations leads. We find the repetitive, rules-heavy work where AI pays back fastest.
04
Generative AI consulting
Where large language models fit, where they don’t, which model to use, and how to keep your data private. Practical advice, not a tour of vendors.
05
Proof of concept
A small, working version of the best idea, tested on real data with clear pass or fail criteria, so you decide on evidence instead of opinion.
06
Build vs buy advice
Sometimes an off-the-shelf tool or your existing Salesforce licence is enough. We say so, and help you set it up.
:: AI readiness assessment
AI readiness assessment: eight questions to answer first
Before spending on AI, answer these. Our readiness assessment works through each one with your team, and the answers decide which use cases go first.
01
Is there a clear business problem?
Start from a cost, a delay or a missed opportunity you can name, not from the technology. “Invoices take four days to process” is a starting point; “we should use AI” is not.
02
Where does the data live, and how good is it?
List the systems and documents the use case depends on. Check whether the data is complete, current and consistent enough for a person to do the job well, because AI needs the same.
03
Can your systems be connected?
AI has to read from and often write to your CRM, ERP or document stores. Systems with APIs make this quick; older or closed systems add work and sometimes change the plan.
04
Who owns the process and the decision?
Every use case needs one person who knows the process, can judge the output and can approve changes. Without an owner, pilots stall.
05
What are the rules on data and privacy?
Agree early which data can go to which AI providers, where it must be stored and who can see the results. This often decides between cloud APIs and models in your own cloud.
06
How will you measure success?
Pick two or three numbers before you start: hours saved, response time, error rate, revenue. Measure them now so you have a baseline to compare against.
07
Who will run it after launch?
AI systems need monitoring, updates and someone to handle exceptions. Decide whether that is your team, a partner or both, and budget for it.
08
What budget and timeline fit?
A first use case is usually worth proving in weeks, not months. Set a budget for a proof of concept and a clear rule for when to scale it or stop.
:: AI implementation roadmap
What the first 90 days look like
A typical strategy engagement, from first workshop to a working proof of concept and a plan to scale it.
Days 1–30
Assess and prioritise
Workshops with each team, a review of systems and data, and a ranked list of use cases scored on value, effort and risk.
Days 31–60
Prove the top use case
A working proof of concept on your real data, tested against a baseline so the result is measured, not assumed.
Days 61–90
Plan the rollout
A costed plan for production: architecture, security, team, timeline and the next two use cases, ready for a go or no-go decision.
:: How it works
How an AI consulting engagement runs
A typical engagement takes four to six weeks from first call to decision.
Week 1
Discovery
Interviews with the people who do the work, a look at your data and systems, and a shared list of pain points.
Week 2
Assessment
Readiness score, risks, data gaps and a long list of use cases, each with a rough value and effort.
Weeks 3 to 5
Proof of concept
We build the strongest idea in a small, isolated form and measure it against tests agreed up front.
Week 6
Plan and handover
A costed roadmap, the PoC code and results, and a recommendation you can act on with us or without us.
:: Cost and timeline
How much does AI consulting cost?
Typical prices for our engagements, based on a senior team at $25 to $35 an hour. Every engagement gets a fixed quote after a short call.
Readiness assessment
$5k – $10k
2 to 3 weeks
A review of your processes, data, systems and rules, ending in a ranked list of AI use cases with rough costs and risks.
Strategy and roadmap
$10k – $20k
4 to 6 weeks
The assessment plus business cases for the top use cases, a target architecture, a security approach and a phased roadmap.
Strategy and proof of concept
$20k – $45k
8 to 12 weeks
Everything in the roadmap plus a working proof of concept on your data, measured against today’s baseline.
What you get at the end
A written report your board can read, a ranked use case list with costs and expected value, an architecture and security plan, and where it applies, working software you can try. You own all of it, whether or not we build the next phase.
What moves the price
Number of teams and processes in scope
How many systems and data sources to review
Security and compliance requirements
Whether a proof of concept is included
On-site workshops or remote only
:: Where AI strategy work lands
Use cases our assessments often rank first
Every company is different, but these come up again and again. Each links to a blueprint showing how we would build it.
Finance
Invoice processing
Read invoices, match them to orders and route only the exceptions to a person.
Read the blueprint
Operations
Demand forecasting
Forecast demand by product and location so buyers order the right stock.
Read the blueprint
Knowledge
Internal knowledge assistant
Answer staff questions from policies and documents, with sources.
Read the blueprint
Lending
Document processing
Pull figures out of bank statements and pay slips and flag what doesn’t add up.
Read the blueprint
Insurance
Claims intake
Read first notice of loss, check the policy and route the claim.
Read the blueprint
Utilities and industry
Predictive maintenance
Spot failing equipment early from sensor and maintenance data.
Read the blueprint
:: Why Sterling
What you walk away with
A readiness report written for managers, not data scientists
A ranked list of use cases with value, effort and risk
A working proof of concept and its test results
A 6 to 12 month roadmap with budget ranges
Advice on models, vendors and data privacy
:: Tools we use
OpenAI
Anthropic Claude
Google Gemini
Llama
Azure OpenAI
AWS Bedrock
Salesforce Einstein
Python
LangChain
4.9
Average rating on Clutch · 350+ projects since 2019
:: Questions
Questions about AI consulting
How much do AI consulting services cost?
What is an AI readiness assessment?
How is AI strategy consulting different from AI development?
Do you only recommend things you can build?
Do we need clean data before we start?
What does an AI strategy consultant do?
How long does an AI readiness assessment take?
What do we get at the end of an AI consulting engagement?
Should we start with consulting or go straight to development?
Can you help us choose between Copilot, ChatGPT Enterprise and custom AI?
How do we measure the ROI of AI?
:: Related AI services
Other ways we can help
AI software development
Custom AI products and internal tools, built to production
AI agent development
Agents that complete tasks inside Salesforce, ERP and email
Generative AI development
LLM apps, RAG and fine-tuning on your data
AI integration services
Connect AI to Salesforce, ERP and internal systems
Send us your brief. We’ll help turn it into reality
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