AI & automation
Put AI where the boring work is.
Not a chatbot for the sake of it. We find the repetitive work inside your business and automate it — with the same tools we teach in our Gen AI courses.
The problem
A coaching institute answers the same 40 admission questions on WhatsApp, every day, by hand. A distributor types supplier invoices into Tally one line at a time. A clinic's receptionist spends two hours a day just handling appointment calls.
None of that work needs a person doing it repeatedly — but it does need someone who understands both the process and the AI tooling well enough to automate it safely, without breaking what already works.
That is the whole service: find the repetitive work, prove it can be automated on a real workflow, then scale what's proven.
What we do
| Capability | What you get |
|---|---|
| Process audit for automation | A written map of your workflows with hours saved and cost per hour, ranked |
| Document & data extraction | Invoices, bills, forms and PDFs turned into structured data in your existing system |
| Customer-facing assistants | WhatsApp / website assistants trained on your own documents, escalating to a human |
| Internal knowledge assistants | Ask-your-own-documents search for SOPs, policies and catalogues |
| Report & content automation | Recurring reports, listings and descriptions generated and human-reviewed |
| Workflow integration | Connecting the AI step into Tally, Sheets, CRM, ERP or email |
| Custom model & RAG pipelines | Built where off-the-shelf tools genuinely don't fit |
How we work
Fixed fee, about a week — you keep the report whether or not you hire us next
2-4 weeks on a single, measurable process
Compared against the baseline set in the audit, not a guess
Roll the proven pattern out to the next workflows
Ongoing oversight so quality doesn't quietly drift
Engagement models
| Model | Best for | Basis |
|---|---|---|
| Automation audit | Deciding if automation is worth it | Fixed fee; report is yours regardless of what you decide next |
| Pilot | Proving one workflow works | Fixed fee per workflow |
| Build & handover | A defined automation, delivered and owned by you | Quoted after the pilot |
| Managed automation | Ongoing operation and monitoring | Monthly, model/API costs passed through at cost plus an agreed margin |
The audit is a fixed, published fee; everything after it is quoted against a measured baseline, never a guess. LLM API usage is always billed at cost plus an agreed margin, disclosed upfront — surprise API bills are the fastest way to break this kind of relationship.
**What AI can't do for you.** It can't fix a process nobody follows. It can't work on data that doesn't exist or lives only in someone's head. It won't replace judgment on your highest-stakes decisions. If an automation isn't going to save you real hours, we'll tell you in the audit and you shouldn't buy it.
What you get
- ✓ Written automation audit with ranked opportunities
- ✓ A working pilot on one real workflow
- ✓ Before/after measurement against a stated baseline
- ✓ Documentation of what was built and how it runs
- ✓ Handover of access, prompts and pipeline configuration
Tech & tools
Who this is for
- ✓ Businesses drowning in repetitive manual work with no time to fix it
- ✓ Teams that already tried a chatbot once and it went nowhere
- ✓ Anyone who wants a measured pilot before a bigger commitment
Who it's not for
- ✕ Anyone expecting AI to fix a process nobody actually follows
- ✕ Anyone wanting a "set it and forget it" black box with no reporting
How we've approached work like this
Anonymised summaries; some are illustrative of our approach.
The problem: 40+ repeat admission questions a day on WhatsApp, handled manually by two staff.
What we did: A WhatsApp assistant answering from their own course and fee documents, escalating anything unusual to a human.
The result: Several hours a week returned to the front-office team; response time from hours to seconds.
The problem: Supplier invoices retyped into Tally by hand every day, prone to entry errors.
What we did: A document-extraction pipeline reading invoice PDFs and pushing structured entries into Tally for review before posting.
The result: Illustrative worked example — not a completed engagement — to show how this would be scoped.
Questions, answered
Where does our data go?
It stays within the pipeline we build for you; we specify storage and retention in writing before the pilot starts.
Do you train models on our data?
No. We use your data to configure and test your automation, not to train shared or third-party models.
Are on-premise or local model options available?
Yes, where the workload and budget support it — this is scoped during the audit.
What does it cost to run monthly?
Managed automation is a monthly fee plus API/model costs at cost, passed through with an agreed margin, itemised.
How do you measure whether it worked?
Against the baseline set in the audit — hours, error rate or response time, whichever the workflow is measured on.
What happens when the model gets something wrong?
Escalation to a human is built into every customer-facing assistant from day one, not added after a complaint.
Let's talk about ai automation.
On a 30-minute call we talk through your actual workflows and tell you honestly whether automation would save you real hours.
Book a consultation
Tell us what you're trying to do. A 30-minute call, no obligation — we'll say honestly whether we're the right fit.
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