AI consulting that ends in a working build
Advice from the people who build and run the workflows
Tenaxity is an AI consultancy for growing businesses in the UK and US. We help you decide where AI is worth using and check you are ready, then implement, integrate and monitor the workflows ourselves, so the plan does not stop at a slide deck.
How our AI consulting differs from a big consulting firm
Large consulting firms are good at enterprise-wide strategy, change programmes and board-level reports. Growing businesses usually need something narrower: a clear view of which jobs AI can take on this quarter, and someone to build them properly. That is the gap our AI consulting services are designed to fill.
Same team from advice to build
The people who assess your workflows are the people who build them, so every recommendation is grounded in what is practical with your tools, data and budget.
Working output, not just a report
Every engagement ends with something concrete: a scoped build, a working workflow or a change to one you already run. If we recommend something, we can show how it would work.
Monitoring after launch
AI workflows need watching. Prompts drift, connected tools change and volumes grow. We keep monitoring and improving what we build rather than handing it over and walking away.
Ways to work with us
Most clients start with the free audit and move on to whichever stage fits. You do not need every stage, and nothing here is a long programme by default. Think of us as an AI automation consultant and build team in one. Monthly packages for ongoing builds are on the pricing page; larger projects are quoted after the audit.
Free AI workflow audit
A free session where we look at your current workflows, tools and bottlenecks, and identify the one or two automations most likely to repay the effort first.
Readiness and roadmap
A structured review of your data, processes, people and risk, ending in a prioritised roadmap: what to automate, in what order, with which controls, and what to leave alone.
Implementation
We build the workflows and agents on the roadmap, test them on real examples and roll them out with approval steps so your team stays in control.
Integration
We connect AI steps to the systems you already run, such as your CRM, inbox, helpdesk, finance tools and shared drives, so the work happens where your team already is.
Ongoing optimisation
Monitoring, fixes, prompt and rule updates, and new automations as the business changes. This is usually covered by one of our monthly packages.
Not sure which you need?
Start with the audit. We will tell you plainly if AI is not the right answer for a process, or if a simpler fixed workflow would do the job better.
AI readiness: the four things we check
Before recommending a build, we check whether the business can support it. Readiness is not about having a data science team. It is about whether the inputs are reliable, the process is clear and someone owns the result.
Data
Where the information a workflow needs lives, how clean it is, and whether it can be reached through an API, an export or a shared drive. Messy data is common and usually fixable, but it changes the order of work.
Processes
Whether the job is done the same way each time, who does each step and where the exceptions are. If a process only lives in one person's head, we write it down before automating it.
People
Who will review AI output, who owns the workflow once it is live, and what the team needs to know to trust it. Projects fail more often from unclear ownership than from bad technology.
Risk
What could go wrong, how costly a mistake would be and which steps must always have a person in the loop. This includes personal data, client confidentiality and any rules in your sector.
Implementation: from roadmap to running workflow
As your AI implementation consultant, we follow the same delivery steps on every build, whether it is a single email workflow or a set of custom AI agents working together.
Scope
We agree the inputs, outputs, owner and how success will be judged.
Design
We map each step and decide which parts need fixed rules and which need AI.
Build
The workflow is built, usually in n8n with language model steps where the work involves reading or writing text.
Test
We run it on real past examples and compare the results with what your team did.
Pilot
A small group uses it with approval steps on, and we fix what they find.
Launch
Use widens, and steps you are confident in move from approval to automatic.
Monitor
Logs, errors and running costs are checked so problems show up early.
Improve
We review edge cases and change prompts, rules and tools as the business changes.
AI integration services: connecting the tools you already use
Most of the value in AI comes from where it is connected, not which model it uses. Our AI integration services link language models to your existing systems through their APIs, webhooks or exports. We usually build on n8n, which works with a wide range of apps and can be self-hosted when data residency matters.
CRM and sales
We can connect to HubSpot, Pipedrive, Salesforce and similar CRMs to log emails, summarise calls, tidy records and flag deals that have gone quiet.
Inbox, chat and documents
Gmail, Outlook, Slack, Microsoft Teams, Google Workspace and Microsoft 365, for triage, drafting, approvals and finding information across shared drives.
Finance, support and operations
Accounting, helpdesk and project tools with an API, for invoice checks, ticket routing, status updates and reporting. If a tool has no API, we look at exports, email parsing or another route.
Governance and risk
Good AI governance for a growing business is practical, not a policy binder that nobody reads. These controls are part of every build, and we agree them with you before anything goes live.
Data protection
- Personal data mapped before any build starts
- Minimum access for each workflow and agent
- Credentials kept in the workflow platform, not in prompts
- Self-hosting options where data residency matters
- Data handling agreed with you, with your data protection lead making the final calls
Approvals and human review
- Approval steps for anything that sends, pays, deletes or changes key records
- Human review of AI drafts until results are consistent
- Logs of every input, decision and action
- Fallbacks that route uncertain cases to a person
- Regular review of errors and edge cases
A worked example
This is a hypothetical firm, used to show how an engagement could run and the arithmetic behind it, not a client result.
Audit and roadmap
For example, say a 20-person professional services firm wants to use AI but has no clear starting point. The free audit finds three candidates: inbox triage, meeting notes to CRM and a weekly client report. The roadmap puts inbox triage first because it touches the most people.
Implementation
Say four people each spend 45 minutes a day sorting and logging shared-inbox email. That is 180 minutes a day, or 15 hours over a five-day week. With an AI triage workflow doing the sorting and logging, each person spends 10 minutes a day checking it: 40 minutes a day, or 3 hours 20 minutes a week.
What changes
Under those assumptions the firm saves about 11 hours 40 minutes a week. The second and third workflows on the roadmap are then built in turn, each with its own approval points and owner.
Questions to ask any AI consulting firm
Whoever you work with, these three questions tell you a lot about whether the advice will turn into something that runs. You can see examples of what we have built in our case studies.
Who builds it?
Ask whether the people advising you will build the workflows, or hand a report to someone else. The gap between strategy and delivery is where most projects stall.
What happens after launch?
Ask who monitors the workflow, who fixes it when a connected tool changes and who reviews its errors each month.
How are mistakes controlled?
Ask where people approve, what gets logged and what the system is never allowed to do. Clear answers here matter more than which model is used.
FAQs
Short answers for teams deciding whether AI consulting is the right next step.
What does an AI consultancy do?
An AI consultancy helps a business decide where AI is worth using, checks whether its data and processes are ready, and plans how to implement it safely. At Tenaxity the same team then builds, integrates and monitors the workflows.
How is Tenaxity different from a large AI consulting firm?
We focus on growing businesses and practical builds. The people who assess your workflows are the people who build them, and we keep monitoring what we build after launch, so the advice stays tied to what can actually be delivered.
Do we need to be technical to work with you?
No. You need to know how the work is done today and who owns it. We handle the technical design, build and integration, and explain each workflow in plain language.
What is an AI readiness assessment?
It is a review of four things: your data, your processes, your people and your risks. It shows which jobs are ready to automate now, which need groundwork first and which should stay manual.
Do you only give advice, or do you build too?
We build. Every engagement is aimed at a working result, whether that is a scoped build plan, a live workflow or an improvement to one you already run.
How much does AI consulting cost?
The first audit is free. Monthly packages for ongoing builds are listed on our pricing page, and larger projects such as multi-agent systems are quoted after the audit, once the scope is clear.
How do you handle data protection and risk?
We map personal data before building, give each workflow the minimum access it needs, keep a person approving anything sensitive and log every action. Data handling is agreed with you during scoping, and your own data protection lead makes the final decisions.
How do we get started?
Book a free AI workflow audit. We look at your workflows, tools and bottlenecks, and suggest where to start and what to leave alone.
Work with an AI consultancy that builds what it recommends
Book a free audit and we will map your current workflows, point to the automation most likely to pay back first, and outline the controls before any build starts.