02 / Automate
The work thatruns itself.
AI agents and automation that actually remove work from your team's day. Not another dashboard to check. We wire up the systems that qualify leads, answer support, and move data between the tools you already use.
Running now. One run in four goes to a human.
Your team's week, rewired.
~0hrs / wk back, per person
Re-enter the same lead across four tools
4 hrs / wk
One record, synced the moment it changes
auto-handled
Answer the same twenty support questions
6 hrs / wk
The agent replies, cites the policy, logs the run
auto-handled
Chase quotes and follow-ups by hand
3 hrs / wk
Sequenced automatically, escalated when it stalls
auto-handled
Copy orders into the fulfilment sheet
2 hrs / wk
Written straight through, reconciled nightly
auto-handled
Watch for the edge cases that break things
always on
Flagged the second they happen, not the day after
auto-handled
Make the calls only you can make
the actual job
Still yours. The agent routes them to you.
stays human
Our approach
An automation that needs babysitting isn't automation. We build systems that fail loudly, log everything, and only ever touch the work that's actually repetitive, never the judgment calls.
How a run actually flows.
Work comes in
- Email & chat
- Voice calls
- Form & webhook
- CRM events
The agent
- 01Classifywhat is this, and how sure am I
- 02Retrievethe order, the policy, the history, via RAG
- 03Decideagainst a confidence threshold you set0.0threshold 0.851.0
- 04Actone call: reply, update, route, or escalate
Written back to
- Your CRM
- Helpdesk & inbox
- Sheets & billing
- n8n / Make / Zapier
Below the threshold, it routes to you. About one run in four.
What we wire up.
AI Agent Development
Purpose-built agents wired into your data and actions, not a chat window
Business Process Automation
The repetitive multi-step work, mapped once and handed off
Sales & CRM Automation
Leads qualified, routed and updated without a hand touching them
Customer Support Agents
First-line answers with citations, escalation on doubt
Voice Agents
Inbound and outbound calls handled end to end
RAG Systems
Retrieval that makes a model genuinely useful over your knowledge
n8n / Make / Zapier
The glue between tools, built to survive a schema change
Custom Integrations
Direct API work when the off-the-shelf connector isn't enough
What it moves, measured.
0%
of repetitive work removed
24/7
agent coverage
<1d
to a working prototype
How we build one.
- 01
Map the workflow
We shadow the actual process, clicks and tools and exceptions, before proposing what to automate.
- 02
Prototype the agent
A working version running against real data within days, not a proposal deck.
- 03
Test on the edge cases
The exceptions are where automations break, so we stress-test those first, not last.
- 04
Deploy with guardrails
Monitoring, a fallback to a human, and logs you can actually audit, from day one.
02 / Automate
AI agents and workflows that remove work, not just add tools.
Automation should take work off your team's plate, not add another dashboard to check. Medhya Labs builds AI agents and workflow automation that run in the background: qualifying and routing inbound leads, answering first-line support, keeping your CRM and other tools in sync, and moving data between systems that were never designed to talk to each other.
We work with the stack you already run. That means integrating with your CRM, helpdesk, spreadsheets, and internal tools rather than asking you to migrate to use automation at all. The output is a system with a clear owner, real logging, and defined points where it hands a decision back to a person.
How we approach it
Every project starts by shadowing the actual process, clicks, tools, and exceptions included, before anything is proposed for automation. The exceptions matter most: they are where automations quietly break, so we stress-test them first rather than last.
You see a working prototype against real data within days, not a proposal deck. Once the logic is right, it ships with guardrails: confidence thresholds, a fallback to a human, monitoring, and an audit log from day one. Nothing customer-facing goes out unchecked by design.
For anything that needs to reason over your own documents or data, we build the retrieval, actions, and memory layer, a RAG system, that makes a model genuinely useful inside your business rather than a generic chat window bolted to the side.
This is for you if
- Your team re-enters the same data across three or four tools every day
- Leads that arrive outside business hours sit until someone gets to them
- You have a Zapier or Make chain that nobody remembers how to fix
- Support tickets stack up behind a form with no triage
- You have tried ChatGPT for a workflow and hit the wall where it isn't wired into anything
Related
- See it in a real system: Knwdle
Deterministic workflows and cross-system sync inside a live platform.
- Build
We build the product the automation runs inside.
- Operate
Keep the agents monitored and tuned every week.
The questions we always get.
The rest, we'll answer on the first call.
No. It removes the repetitive 60% so your team spends time on the judgment calls only they can make.
Every agent ships with confidence thresholds and human escalation paths. Nothing customer-facing goes out unchecked by design.
Yes. We integrate with the CRM, helpdesk, and stack you already run. We don't make you migrate to use automation.
A chat window isn't wired into your data or your workflow. We build the plumbing (retrieval, actions, memory) that makes the model actually useful inside your business.
Other capabilities