Customer-support triage
A step that reads incoming requests from email, forms or chat, works out what they are about, tags and routes them, and drafts a reply for an agent to approve. Urgent or unusual items go straight to a person.
AI automation
AI automation consulting for any industry
IT-Labs helps businesses find the work AI can reliably take on, builds it, connects it to the systems they already use and keeps a person in control. We work with any AI model or provider.
The website as your AI consultant
Ask the AI advisor
Describe your business and the work that takes up your team's time, and the advisor will suggest where AI automation could help, with the review and guardrail points. It is an AI and it can be wrong, so treat its answers as a starting point for a conversation.
Why now
What has changed, and what has not
Software can now read and write ordinary business text. That makes practical a long list of tasks that used to need a person: working out what an email is about, pulling fields out of a PDF, drafting a reply, answering a question from a policy document.
It does not make every process a candidate. Models make mistakes, and the cost of a mistake differs from task to task. The useful work is choosing tasks where a first pass by AI, checked by a person, is faster and no less safe than doing it by hand, and then building the checks around it.
The places this helps are rarely glamorous: the shared inbox, the pile of invoices, the weekly report. That is where we start.
What has changed
- Software can handle free text and documents
- Many models are available, including ones you can host yourself
What has not
- You still need integration, permissions and testing
- Someone still has to be accountable for the result
Our approach
Five steps, run as a loop
We start small and prove it on your own examples before anything is widened. After the first pass the loop repeats for the next workflow.
Assess
We look at how the work is done today, what information it uses and where it goes wrong. You get a short written view of where AI fits and where it does not.
Prioritise
We rank the candidates by value, risk and effort, and choose one workflow to start with, with success criteria agreed in advance.
Pilot
We build a working version and run it alongside the manual process on your real examples. A person reviews everything at first.
Integrate
We connect it to your email, documents, databases and business systems, with permissions, logging and fallbacks.
Operate
We monitor quality and cost, handle changes, and widen the scope step by step as trust builds.
What typically gets automated
Six places we usually begin
These are examples of what we can build, not a record of past client work. Which ones fit depends on your data and on how costly a mistake would be.
Document and email processing
Reads invoices, orders, forms and emails, extracts the fields you need, checks them against your records and enters them into your systems. Anything it is unsure about is queued for a quick human check.
Reporting and data entry
Recurring reports assembled from several systems with a short written summary of what changed, and data moved between tools without anyone retyping it.
Scheduling and follow-ups
Proposes times, sends reminders, chases outstanding replies and updates the record. Replies it cannot interpret are passed to a person.
Quality and compliance checks
Compares work, documents or records against your rules and checklists, and flags exceptions with the reason, for a reviewer to decide.
Internal knowledge search
An assistant that answers staff questions from your own policies, manuals and past cases, shows its sources and respects who is allowed to see what.
See what this looks like in your sector on the industries page.
Keeping it safe
Human review, limited access and a record of everything
Human review by design
Anything that matters goes to a person before it is acted on. We set the review threshold with you, and tighten or loosen it as evidence builds.
Access control
The automation sees only what it needs, with its own credentials and least-privilege access to each system.
An audit trail
We log what the AI saw, what it produced and who approved it, so any outcome can be checked afterwards.
Your data stays yours
You decide where models run, including on your own infrastructure. We design to minimise what any hosted model sees, and the code and data are yours.
We do not claim formal certifications. We apply careful, standard engineering practice and explain the trade-offs in plain English.
Working together
Start with a conversation, then a written estimate
Free consultation
A conversation about your work and your systems. We tell you honestly what looks suitable, what does not and what we would do first.
Written estimate
A written scope and estimate for an assessment or a pilot, before you commit to anything. We do not publish prices because the right number depends on your scope.
Assess, pilot, operate
Short milestones with demos. Fixed price where the scope is clear, time and materials where it will evolve, and a monthly arrangement once it is live. How we work.
The website as your first consultant
AI automation readiness checklist
Eight questions, about three minutes. It is worked out in your browser: nothing you tick is sent or stored. You get three places we would look first and a rough readiness level.
This checklist needs JavaScript to calculate a result. You can still use it as a list: send your answers to sales@it-labs.in or use the contact form, and we will reply with a short assessment.
- Which best describes your organisation?
- Professional services (consulting, legal, accounting, agency)
- Finance, insurance or trading
- Retail or e-commerce
- Manufacturing or engineering
- Logistics or transport
- Healthcare or clinics (administrative work)
- Education or training
- Software or technology company
- Something else or a mix
- Which kinds of repetitive work take the most time? Tick all that apply.
- Answering and sorting customer or staff requests
- Reading emails, forms, invoices or other documents and keying the data in
- Building reports, or copying data between spreadsheets and systems
- Scheduling, reminders and chasing follow-ups
- Checking work against rules, policies or standards
- Finding answers in past documents, policies or tickets
- None of these stand out
- Where does the information for that work mostly live? Tick all that apply.
- Email and attachments
- Documents and PDFs
- Spreadsheets
- A database or business system
- Customer messages, chat or tickets
- Paper, or mostly in people's heads
- How would you describe the systems and tools involved?
- Mostly cloud tools that have APIs or exports
- A mix of modern and older or desktop software
- Several tools that do not talk to each other, so people copy data between them
- Mostly older systems, spreadsheets or paper
- How often does this work come round?
- A few times a month
- Weekly
- Daily, dozens of items
- Constantly, hundreds of items a day or more
- How sensitive is the data involved?
- Public or low-sensitivity information
- Internal business information
- Personal or customer data
- Regulated or highly confidential data (for example health, financial or legal)
- Who would review the results before they are used?
- A named person or team would review them
- We would spot-check from time to time
- Not decided yet, or nobody has time to review
- When would you like to see something working?
- As soon as possible
- Within 1 to 3 months
- Within 3 to 6 months
- Just exploring for now
How the result is worked out
It is a fixed set of rules, not a hidden model. Each question adds to one of these scores:
- points = need + data + systems + volume + oversight (0 to 13)
- need (0 to 3): one point for each kind of repetitive work you tick, up to 3
- data (0 to 3): one point for each digital source you tick, minus one if information is mostly on paper or in heads, up to 3
- systems (0 to 2): 2 for cloud tools with APIs or exports, 1 for a mix or for disconnected tools, 0 for mostly older systems or paper
- volume (0 to 3): 0 for a few times a month, 1 weekly, 2 daily, 3 constant
- oversight (0 to 2): 2 for a named reviewer, 1 for spot checks, 0 if undecided
Your readiness level is then:
- Starting: points are 5 or fewer, or need is 0, or data is 0
- Ready to pilot: everything else
- Ready to scale: points are 10 or more, oversight is at least 1, data is at least 2 and sensitivity is not "regulated"
The three candidate areas are the three with the highest weights from your industry, the kinds of work you ticked (3 points each), your data sources and your systems. Ties go in the order shown on this page. Questions you leave unanswered count as zero, and at least six must be answered.
Find out what AI could take off your team
Describe the work and the systems involved. We offer a free consultation and a written estimate, and you will talk directly to the developer who would build it.