Less busywork. More work done.
We build AI assistants and automations that read incoming information, route work, prepare responses, and keep your systems up to date. Designed around your process, with clear ownership from start to finish.
AI & automationRibhu Labs builds AI workflows that turn incoming documents, messages and requests into organised, assigned work, with every decision visible to the people responsible. Most engagements start with a one-week Workflow Review of a single process.
Start with
the real work.
Enquiries wait in inboxes. Documents need sorting. People copy the same information between tools. The cost is not just time: context gets lost and the next person has to start again.
We map the workflow, connect the tools you use, and build the steps that move it forward. Rules handle predictable decisions; AI helps interpret varied documents and language. We test real examples and exceptions, then put the working system in the hands of the people who use it.
A decision you can follow.
Explore a simplified example. These demonstrations explain an approach; they are not connected to live systems.
Give the right work to the right person.
A new enquiry becomes a structured record, a suggested route, and a draft for review.
- Capture
- Understand
- Review
- Act
Select an input, then follow its path.
What we
can deliver.
Scope is agreed around your systems, constraints, and intended outcome.
- 01
A workflow map covering triggers, decisions, exceptions, and owners
- 02
AI assistants, document processing, and integrations for the agreed workflow
- 03
Review queues, permissions, and an activity record for automated actions
- 04
Acceptance checks, operating instructions, and a team handover
From question
to capability.
- 01
Map the repeated work
Follow a real request from arrival to completion. Identify delays, duplicate effort, and the information each step needs.
- 02
Build the working flow
Connect the systems, implement the decisions and actions, and test the normal path alongside missing or uncertain inputs.
- 03
Put it into practice
Check the results with your team, agree who maintains the workflow, and roll out the tested scope.
A little more
clarity.
Does every automation need AI?＋
No. Rules work well for fixed calculations, routing conditions, and required fields. AI is useful when the workflow needs to interpret varied language, images, or documents.
Can we choose what needs approval?＋
Yes. We define which steps run automatically, which need review, and who can approve them. Those boundaries are part of the workflow design.
Can you work with our existing tools?＋
We review the interfaces and access available in your current systems, then design the integrations around them. The aim is a connected workflow your team can operate.
Workflow Review
We map one process with the people who do it, and mark where a rule, a model, or nothing at all belongs.
You get: A process map, a shortlist of changes and a clear go or no-go. Yours to keep, whoever builds it.
4 weeksPilot Build
One working piece built on your own data or task: tested with your team, documented, and handed over with training.
You get: A working system for one process, its source and documentation, and a team that can run it.
Half a dayTeam Workshop
A hands-on session using your own examples: where AI fits, how to map an automation, how to check a result.
You get: A shared vocabulary and two or three candidate processes worth reviewing.
Does this task need AI, or is a simple rule enough?
Use a rule for a fixed, explicit condition. Reach for AI only when the input varies and needs interpretation first.
How do you map a workflow before automating it?
Trace one real request from trigger to completion, note every step and handoff, then decide what to automate.
What should you ask before hiring an AI automation studio?
Ask about scope, data access, who owns the code and data, handover, failure handling, and what happens after launch.