One assistant in your team chat that answers from your files and shows the source
Actions it can take for staff: raise a request, update a record, draft a reply
Roles, so the warehouse sees stock and finance sees money
Approval cards for anything that changes a record or reaches a customer
For example, in your trade
Store managers ask the assistant for stock at another branch, and it raises the transfer for the area manager to approve.
Consultants ask in the team group what a case needs next, and the assistant answers from the case file with the source.
Front desk staff ask in Hindi where a guest's late checkout request stands and get the answer from the booking system.
What we never promise
Never promise it knows what isn't written down; where the answer isn't in your files it says so and asks a person. On WhatsApp it stays a service of your business, answering from your own records; a general purpose assistant runs in your own app, the browser, Slack or Teams, because WhatsApp's business platform has barred those since 15 January 2026.
What we have built that shows it
Agent in the team chat, built for a relocation company with teams across India.
Employee mission control, built for a relocation company with teams across India.
A lead agent that splits the job into parts and hands each one to a specialist
Specialist agents for reading, pricing, compliance and writing, each with its own tools
A checker agent that tests every part against your rules before it reaches you
One board showing each part, which agent has it and what's waiting for you
For example, in your trade
A 300 page tender is read, priced against your rate book and drafted into a bid, with every exception marked for your estimator.
An audit firm's year-end file is split by section and each part is checked against last year's working papers, with gaps listed for the partner.
A power company's environmental clearance file is split by chapter, each part is checked against the rules, and the gaps are listed for the project head.
What we never promise
Never promise a bid or audit file goes out unread; agents draft and check, and a qualified person signs.
What we have built that shows it
A team of AI agents that plans, builds and checks software, built for our own company.
A list builder that turns your question into a row per item and a column per fact
Agents working in parallel that visit each website, catalogue or registry and fill the row with its source
A confidence mark on every cell, so you check the doubtful ones first
Exports to your sheet or CRM, refreshed on a schedule
For example, in your trade
Every certified organic turmeric supplier in three states, with capacity, certificates and contact, in one sheet by Monday.
Every commercial listing above 5,000 square feet in two micro markets, with rent, floor and owner type, refreshed weekly.
Prices of your 300 best sellers on five marketplaces, checked every morning, with the gaps marked.
What we never promise
Never promise every row is right; public sources go stale, so each cell shows its source and date and doubtful ones are flagged. We read sites only within their terms and never get around a login or a captcha.
A setup that gives each person an agent in under a minute, with their role and duties
Shared how-to steps the company writes once and every agent follows
Company guardrails: what data each role sees and what needs a yes
A usage view that shows which agents save time and which sit idle
For example, in your trade
Every account manager at a 60 person agency has an AI agent that drafts the weekly client report from the project tracker.
At a leadership workshop, each delegate scans a card and gets an AI agent that knows their role.
What we never promise
Never promise everyone will use it; we measure use per person and fix or remove the agents nobody needs. On WhatsApp it stays a service of your business, answering from your own records; a general purpose assistant runs in your own app, the browser, Slack or Teams, because WhatsApp's business platform has barred those since 15 January 2026.
What we have built that shows it
An agent for every delegate in a room, built for an industry body in Asia Pacific, at a leadership workshop.
A morning brief on the owner's phone: today's meetings, the mails only the owner can answer and what's overdue
Meetings booked, moved and declined by a message, inside the rules you set for your week
Every mail sorted, with replies drafted in the owner's own words and waiting for a tap
A one page brief before each meeting: who they are, what was said last time and what's still open
Every promise made in a meeting or a mail tracked, with a nudge to whoever owes it
For example, in your trade
A plant owner gets a two minute brief at 7am with the day's buyer meetings, the three mails only he can answer and a supplier who missed the date he promised.
A law firm's managing partner sends a voice note asking for lunch with a client next week, and her AI chief of staff offers three slots and books the one she taps.
Before every site meeting a developer's MD reads one page on the contractor: last month's promises, the bills waiting and the delay on block C.
What we never promise
Nothing is sent, booked or paid without the owner's tap, it reads only the accounts the owner connects, and on WhatsApp it never runs as a general assistant.
What we have built that shows it
Mail engine, built for our own company.
Calendar where a sentence becomes a meeting, built for our own company.
Meeting memory, built for our own company: every promise picked out with its quote, waiting for a person to confirm.
The role written with the hiring manager as the experience and skills that really matter
A search of public professional profiles, your past applicants and staff referrals for people who fit
A shortlist with the evidence for each match and what still needs checking
A personal first note to each person, drafted for your recruiter to edit and send
Opt outs and do not contact lists kept, and where each name came from recorded
For example, in your trade
A cement company finds plant heads with kiln experience in three states, including two who applied for another role last year.
A hospital group finds ICU nurses with the right registration who live within an hour of its new branch.
An IT services firm finds engineers with payments experience in Pune for a bank project, with a note to each about the work.
What we never promise
We use only profiles people made public and your own applicant records, honour every opt out, never score age, gender, caste or religion, and a recruiter sends every message.
A plant owner gets a two minute brief at 7am with the day's buyer meetings, the three mails only he can answer and a supplier who missed the date he promised.
A law firm's managing partner sends a voice note asking for lunch with a client next week, and her AI chief of staff offers three slots and books the one she taps.
A power company's environmental clearance file is split by chapter, each part is checked against the rules, and the gaps are listed for the project head.
We never name a client or show how they run inside. Each piece says what kind of company it was built for, and every number says what it counts and when.
Team chatMoves desk
Waiting for the owner
Rohan
Can someone tell the Menon family when their shipment clears?
AI agent
It cleared customs this morning. I have drafted a note to the family from the case file.
From the case file, 11 Oct
For the ownerWaiting for your yes
Send the update to the Menon family?
GoStop
Shown with sample dataNothing runs until the owner says go
Built for our founder's own work, in June 2026, before Agentec
Over twenty nights, a team of five AI agents worked while our founder slept: one on open projects, one turning the day's mistakes into lessons, one scouting new tools and one weighing new AI models against ours.
68overnight reports filed across 20 nights by a five agent team. 15 Jun to 8 Jul 2026.
Ran 15 Jun to 8 Jul 2026
111tested promises in its database, one of them that a read across clients is refused. Read 11 Oct 2026.
Built for an industry body in Asia Pacific, at a leadership workshop
Every delegate scanned a card and described an AI agent for a job in their own firm, then saw which of their tasks to automate, which to govern and which to keep human.
30 of 30spoken commands matched to the right button in a measured run, 4 of them rightly to nothing. Measured 24 Sep 2026.
Name the job your team does every day. We'll build the agent that does it.
45 minutes on a video call with our founder and the people who live with the problem. Nothing to sign. You leave knowing what we would build first, and why.