01
AI opportunity assessment
We map how work flows through your business, talk to the people who do it and list the tasks where AI could save time, reduce errors or improve service.
From assessment to rollout
AI consulting that ends in something running
We help you decide where AI is worth using, check your data is ready, choose between building and buying, then run a pilot and roll it out with sensible governance. The team that advises you can also build it, so the plan stays grounded in what can actually be delivered.
Thanks, that’s with us.
A senior engineer reads every enquiry and will reply as soon as they can.
Want to take it further now?
Book a time that suits you, or send a message on WhatsApp.
- Honest advice, including when AI is not the answer
- One team from first assessment to rollout
- Written quote with scope and exclusions agreed up front
- “I was impressed by their ability to deliver unparalleled quality at an extremely fast pace and for great value.”ClutchAngelos BougasManaging Director, Ocley Group
- “Shahrukh did an excellent job creating a fully customized portal for my car auction business…FiverrMichael JonUnited Kingdom
- “I absolutely love the way Shahrukh works! He is a pro at handling React and Django features…UpworkJohnson C.React / Django feature build
- “The team responded to comments immediately, and corrected the mistakes exactly as I provided the comments.”ClutchGiorgi MumladzeFounder/CEO, Club Confide
Free
First 30-minute call
Written
Quote with scope agreed up front
Yours
Reports, code and prompts
One team
From advice to build
Technologies we build with
- OpenAI GPT
- Anthropic Claude
- Google Gemini
- Azure OpenAI Service
- AWS Bedrock
- ChatGPT
- Microsoft Copilot
- Zapier
- Make
- n8n
- Python
- LangChain
- LlamaIndex
- MCP
- pgvector
Quick answer
What is AI consulting?
AI consulting is independent advice on where artificial intelligence will genuinely help your business, followed by a plan to put it into practice. A consultant looks at how work gets done today, which tasks are repetitive or slow, what data you hold and what risks you carry, then recommends a small number of uses worth testing.
Good consulting does not stop at a report. It covers choosing the right use case, checking your data is ready, deciding whether to build, buy or integrate, running a pilot on real work and putting governance in place before a wider rollout. Where AI is not the right tool for a problem, a good consultant says so.
SpiderHunts Technologies Ltd is registered in London (Companies House 16718403), with a remote engineering team. Since 2020 the business has delivered projects for more than 1,000 clients, and we offer consulting alongside the AI integration, agent and automation work we build.
What we cover
AI consulting services: what the engagement covers
You can take the whole engagement or only the stages you need. Each stage ends with something written you can act on, whether or not you continue with us.
02
Use-case selection
Each candidate is scored on value, feasibility, data availability and risk, so you start with one use case that is worth doing rather than ten that sound interesting.
03
Data readiness
We check whether the data a use case needs exists, is accurate enough and can be reached safely, and list what needs fixing before any build.
04
Build vs buy advice
We compare an off-the-shelf tool, an AI feature in software you already pay for, an API integration and a custom build, with the cost drivers and upkeep of each.
05
Pilot
A working version on real data with a small group of users, judged against success measures you agree with us before it starts.
06
Rollout
Integration into your live systems, staff training, monitoring and a plan for the next use case once the first one is working well.
07
Governance
An AI usage policy, approval rules for higher-risk actions, logging and a named owner for each system, designed to support UK GDPR and the other requirements you work under.
Deliverables
What you receive at each stage
Everything is written down and yours to keep, so you can act on it with us, with your own team or with another supplier.
- Deliverable 01
Opportunity map
The processes we reviewed, how your team says time is spent on each, and where AI could realistically help.
- Deliverable 02
Prioritised use-case shortlist
Candidate use cases scored on value, feasibility, data and risk, with a recommended first pilot and the reasons for it.
- Deliverable 03
Data readiness notes
What data each shortlisted use case needs, where it lives, its gaps and the access or privacy issues to settle first.
- Deliverable 04
Build, buy or integrate recommendation
The option we recommend for each use case, the alternatives we ruled out and the main cost drivers, including model usage.
- Deliverable 05
Pilot plan and results
Scope, users, success measures and the evaluation of the pilot against them, with a clear recommendation to roll out, change or stop.
- Deliverable 06
Rollout and governance plan
Integration steps, training, monitoring, a usage policy, approval rules and the named owners who will look after each system.
Choosing a consultant
What to ask before you hire an AI consultant
Before you hire any AI consulting company, ask three things: who will actually do the work, what you will own at the end, and when they would advise you not to use AI at all. A clear answer to the last question is one of the better signs that the advice will be honest.
Many businesses hire AI consultants and a development company separately, and detail can get lost at the handover between them. At SpiderHunts the engineers who assess your processes are the people who can build the pilot, so recommendations stay grounded in what is practical to deliver. You remain free to take the plan to your own team or to another supplier.
Ask too how success will be measured. We agree the measures with you before a pilot starts, using things you already track such as hours spent on a task or the number of errors corrected, so the decision to roll out rests on your own numbers.
Why it matters
Why so many AI plans never reach daily work
Most businesses do not lack AI ideas. They lack a clear choice of where to start, data that is ready, and someone accountable for turning a plan into a working system.
AI without a plan
- A strategy document with nothing running behind it
- Tools bought before anyone checked the data they need
- Staff pasting customer details into public chat tools with no policy
- Pilots that never reach the systems people use every day
- Nobody owns the AI once the consultant has gone
AI with a plan you can act on
- A short list of use cases ranked by value, feasibility and risk
- Data gaps found, with a plan to fix them, before any build starts
- A clear usage policy and approval rules for staff
- A pilot on real work, judged against measures you agreed
- A named owner, documentation and monitoring after rollout
Not sure where AI would help first?
Book a free 30-minute call. We will ask about your work and your systems and tell you honestly whether an assessment is worth doing.
Examples
Where an AI assessment often leads
These are illustrative examples of the use cases an assessment commonly shortlists. Your own shortlist depends on your processes, your data and the risks you carry.
Intake, letters and scheduling
For a clinic or care provider looking for a healthcare AI consulting service, the first questions are where patient data lives, who may see it and which tasks AI should assist rather than decide. A shortlist might include intake triage, appointment handling and summarising referral letters, with clinicians reviewing every output. See also our healthcare software development.
Documents and knowledge
For example, a law or accountancy firm might start with drafting from past work, extracting key terms from contracts, or an internal assistant that answers questions from the firm’s own documents.
Catalogue and customer questions
A retailer might test product descriptions written at catalogue scale, search that understands what shoppers mean, or an assistant that answers order questions and hands harder ones to staff.
Orders that arrive by email
An operator receiving bookings as unstructured emails might pilot extraction into its order system, with a person checking anything the model is unsure about.
Documents and policy questions
A finance team might look at processing onboarding documents, triaging disputes or answering staff questions from its policy library, with an audit trail on every AI step.
Enquiries and listings
An agency might qualify enquiries on web chat and WhatsApp, draft listing descriptions, or pull key dates and terms out of leases into its CRM.
How it works
How the engagement works, step by step
Each stage has a written output and a clear decision point, so you choose whether to continue after every step. Timelines depend on how many teams and systems are involved and are set out in your quote.
Free call
A conversation about your goals, the systems you run and where time goes, and an honest view on whether an assessment is worth it.
Free 30-minute callAssessment
Interviews with the people who do the work, a map of key processes and a review of your systems and data.
Use cases and data
Candidates scored and shortlisted, data readiness checked, and a build, buy or integrate decision made for the first use case.
Pilot
A working version on real data with a small group of users, evaluated against the success measures agreed at the start.
Rollout and governance
Integration into live systems, training, monitoring, a usage policy and named owners, then documentation and handover.
Optional retainer after
Clear scope · Regular demos · Full handover
Is it right for you?
When paying for AI advice makes sense
Consulting earns its cost when there is a real decision to make. If you already know exactly what you need built, it is usually quicker to go straight to the build.
A good fit when
- Your team spends hours each week on repetitive work and you are not sure which parts AI can handle
- Leadership wants a clear plan before spending money on tools
- Staff already use chat tools informally and you want a policy and something properly set up
- You hold sensitive or regulated data and need to know what is safe
- You want the people who advise you to be able to build it too
Probably not the right fit when
- You already know what to build: go straight to AI integration or AI agent development
- The task happens a few times a month and an existing tool already covers it
- Simple rules-based business automation would solve the problem without AI
- You need a figure for the return before anyone has looked at your processes or data
- There is nobody on your side with time to take part in the assessment
Build vs buy
Build, buy or integrate: how we decide
We recommend the simplest option that does the job safely. Often that is a tool you already pay for, not a custom build.
| Option | When it fits | What to watch |
|---|---|---|
| Use an off-the-shelf AI tool | General writing, research or summarising, where the data involved is not sensitive | No access to your systems, so staff still copy and paste; check the vendor’s data terms |
| Switch on an AI feature you already pay for | Your CRM, helpdesk or accounting software already offers the feature you need | Limited to that one tool; check where data is processed and what it costs per user |
| Integrate an AI model into your systems | The work happens inside your CRM, ERP or app and needs your own data (see AI integration) | Needs evaluation tests, access control and cost monitoring |
| Build a custom agent or model | Multi-step work across several tools, or a prediction problem on your own data (see machine learning) | Higher cost and upkeep, so only worth it for frequent, valuable work |
| Do not use AI yet | A process change or plain automation solves the problem, or the data is not ready | Revisit once the data or process is in better shape |
Technology
Tools and models we assess and build with
We are not tied to one vendor. We compare options on your real work and keep the model swappable where we build.
AI models & platforms
- OpenAI GPT
- Anthropic Claude
- Google Gemini
- Azure OpenAI Service
- AWS Bedrock
Off-the-shelf tools we compare
- ChatGPT
- Microsoft Copilot
- Zapier
- Make
- n8n
Build & run
- Python
- LangChain
- LlamaIndex
- MCP
- pgvector
Sectors
Industries we advise on AI
We work remotely with businesses in the UK, the USA, Canada, Europe, the Middle East and Australia.
HealthcareIntake, letters and scheduling, with patient data handled carefully.Fintech & financeDocument processing, dispute triage and policy questions.EcommerceCatalogue content, search and order questions.LogisticsEmail-to-order extraction and exceptions.Real estateEnquiry qualification, listings and lease data.
Where we work
United KingdomUK-registered in London, with UK GDPR-aware data handling.
United StatesWe work with US businesses remotely, by video call.
CanadaConsulting for Canadian businesses, delivered remotely.
EuropeGDPR-aware advice for businesses across Europe.
FAQ
AI consulting FAQs
Straight answers to what buyers ask before they sign.
Still have a question?
Ask us directly. A senior engineer reads every question.
Ask about your projectWhat does an AI consultant actually do?
An AI consultant works out where AI can genuinely help your business and how to put it into practice safely. In our engagements that means mapping your processes, shortlisting use cases, checking your data, recommending whether to build, buy or integrate, and then running a pilot and rollout if you want to go ahead.
How much does it cost to hire an AI consultant?
The free AI automation audit is a short, no-obligation first look. Our paid AI Readiness Audit starts from £1,500, excluding VAT, and ends in a written, prioritised plan. Pilots and builds are quoted in writing after the assessment, with scope and exclusions agreed up front, because their cost depends on the systems and data involved.
How long does an engagement take?
It depends on how many teams, processes and systems are in scope. An assessment of one team is much shorter than one across several departments, and a pilot depends on the use case chosen. We set out the timeline for each stage in your written quote.
Do we need clean data before we start?
No. Checking data readiness is part of the work. Sometimes the right first step is to fix how data is captured or stored before any AI is built, and we will tell you if that is the case.
Should we build a custom AI tool or buy one?
Buy when an off-the-shelf tool or a feature in software you already pay for does the job safely. Integrate or build when the work happens inside your own systems, needs your data, or is frequent and valuable enough to justify the upkeep. We compare the options for each use case and explain the trade-offs in writing.
Will you tell us if AI is not the right answer?
Yes. Some problems are better solved with plain automation, a process change or a tool you already have. Recommending against AI where it does not fit is part of honest consulting, and it can save you from paying for a tool you do not need.
Can you build what you recommend?
Yes. The same team builds AI integrations, AI agents, chatbots, automation and machine learning models. You are not obliged to use us for the build: the plan is yours and can go to your own team or another supplier.
How do you handle sensitive or regulated data?
We look at what data each use case needs and how it should be protected before anything is built. Options include enterprise AI services with no data retention, removing personal details before data reaches a third-party model, or models hosted in your own environment. Designs are built to support UK GDPR, HIPAA or other requirements you work under, with terms such as data processing agreements set per project.
What does AI governance involve for a smaller business?
Usually a short usage policy for staff, clear rules on which AI actions need a person to approve them, logging of what each system does, and a named owner for each system. It does not need to be heavy, but it should be in place before AI touches customer data or decisions.
Who owns the work at the end?
You do. Reports, plans, code, prompts and the accounts with AI providers are yours, and every build ships with documentation and a handover session. An optional retainer is available if you want us to keep monitoring and improving the system.
Do you work with businesses outside the UK?
Yes. SpiderHunts Technologies Ltd is registered in London and works with a remote team, so we advise businesses in the UK, the USA, Canada, Europe, the Middle East and Australia by video call.
Start here
Find out where AI fits in your business
Tell us what your team spends its time on and the systems you use. We will suggest a sensible first step, whether that is the free audit, a paid assessment or no AI at all.
- You tell us what you needTwo minutes on the form, or a message on WhatsApp.
- A senior engineer reviews itAnd comes back with questions, a realistic range and an honest view on fit.
- Free 30-minute scoping callWe talk through scope, options and a realistic estimate, with no obligation.
Thanks, that’s with us.
A senior engineer reads every enquiry and will reply as soon as they can.
Want to take it further now?
Book a time that suits you, or send a message on WhatsApp.