AskDoozy
An AI coworker in Slack that does the work in your real systems.
A startup from India, founded by Shiv Sarthak.
An AI coworker in Slack that does the work in your real systems.
A startup from India, founded by Shiv Sarthak.
This page is designed to help you find out whether AskDoozy is good and if it is the right choice for you.
Doozy is a coworker in your Slack. Mention @Doozy in a thread with a real task ("why was Acme charged twice?", "post signups and churn to #leadership every Monday", "export last month's refunds by reason") and it goes and does the work in your own systems: your database, Stripe, GitHub, Linear, PostHog, WooCommerce, any MCP server, or the web. The answer comes back in the thread with the files and a receipt for every action it took.
Built for support, success and ops teams who otherwise wait on an engineer to pull a number. Setup is self-serve, with no operator and no pasted keys.
Safe to point at production. Every task runs in its own isolated sandbox. Your API keys and database credentials never go into the sandbox; a gateway outside it adds them per request, so the agent cannot leak a key it never had. Database access is read-only. Tools that can delete or overwrite start switched off until a workspace owner turns them on. Every action leaves a receipt and an append-only audit log.
Learns your company as it goes. Notes about your business live in plain Markdown you can read and edit. Schedules run recurring reports. Skills are procedures you write yourself.
One price per workspace. No seats, no credits. Everyone in Slack can use it. 14-day free trial, no card required.
Listed in
Works in your real systems
Mention @Doozy in Slack; it does the task in your database, Stripe, GitHub, Linear, PostHog, WooCommerce or any MCP server
Keys never in the sandbox
Each task runs in an isolated sandbox; credentials are added outside it, database is read-only, destructive tools start off
Receipts and schedules
Every action leaves a receipt in the thread and an audit log; recurring reports run on a schedule
Doozy doesn't just answer questions in Slack, it goes and does the work. Mention @Doozy in a thread with a real task and it works in your own systems (your database, Stripe, GitHub, Linear, PostHog, WooCommerce, any MCP server, the web), then posts the result back in the thread with the files and a receipt for every action. It's built to be safe to point at production: every task runs in its own isolated sandbox that never holds your API keys or database credentials, database access is read-only, and tools that can delete or overwrite start switched off until an owner turns them on.
Choose Doozy if you want an AI that finishes tasks in your own tools, not one that tells you how to do them. It costs one price per workspace with no seats or credits, so everyone in your Slack can use it, not only the people with a licence. Setup is self-serve: a non-technical team lead can install it and connect tools without an engineer or pasted API keys. And it's designed for teams who are nervous about letting AI near production. Credentials stay outside the sandbox, the database connection is read-only, risky tools are off by default, and you get a receipt for everything it did. You can try it free for 14 days with no card.
TypeScript end to end, with Postgres for data, the Slack platform for the interface, and the Model Context Protocol (MCP) for connecting tools. Every task runs in its own short-lived, isolated cloud sandbox. Calls to models, tools and git pass through gateways outside the sandbox that attach credentials per request, so secrets never sit where the agent can read them. The marketing site is built with Astro.
Support, customer success and operations leads at small and mid-sized companies (roughly 10 to 150 people) who work in Slack and usually have no engineering help on hand. They're the people who keep asking "can someone check this?" and waiting hours for an engineer to run a query: why a customer was charged twice, what happened to an order, how many accounts churned last month. Founders and engineers use it too, for investigations, reports and small code fixes that end in a pull request.
At Spur, support kept asking in Slack "why did this customer see this?" and waiting a couple of hours for an engineer to run a query. In July 2026 I built a bot that could go and check itself. On its first day it found the root cause of a broadcast failure in four minutes. Support adopted it faster than engineering did, and people kept asking to connect more tools. Doozy is what I learned from that bot, rebuilt from scratch as a product any team can add to their Slack, with the safety work (no keys in the sandbox, read-only database, receipts) that running an AI against real production taught us we needed.
We have collected here some useful links to help you find out if AskDoozy is good.
Check the traffic stats of AskDoozy on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of AskDoozy on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of AskDoozy's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of AskDoozy on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about AskDoozy on Reddit. This can help you find out how popualr the product is and what people think about it.
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