
AI Content Automation Engine
A content system that drafts blog posts, social posts for six platforms and a weekly newsletter in your brand voice, schedules them, and waits for a person to approve before anything goes out.

Use our open-source tools today, or bring us the workflow that eats your week and we'll build the system that runs it.
Founder-led studio working in Salesforce Agentforce, n8n, Python and Node.
Pick an email, or type a subject of your own, and watch our inbox agent sort it, pull out what needs doing and draft a reply. The answers are recorded from the real agent.
Pick an email on the left to see what the agent does with it.
Each one started as a tool we needed ourselves. Try the demo, read the code, or install it.

A content system that drafts blog posts, social posts for six platforms and a weekly newsletter in your brand voice, schedules them, and waits for a person to approve before anything goes out.

An AI agent that triages your inbox, drafts replies from how you answered before, sends action items to your task app, and never sends anything without your approval.

AI code review on every pull request: comments on the exact changed lines, a summary, and the tests worth adding. A GitHub Action, a CLI and a web UI.

Scaffold production-ready Next.js, Node, Python and Salesforce DX projects, preview every file before you download, and write READMEs from your code with AI.
Start with an audit, prove it in a sprint, then take it to production. Every engagement has a fixed scope and a written plan.
Starting from ₹25,000Starting from $750
A short, focused engagement that tells you which Agentforce use case is actually worth building — and which ones are not.
Includes
Starting from ₹75,000Starting from $2,500
One use case, built and demonstrated as a working agent, so you can prove it before approving a larger implementation.
Includes
Starting from ₹1,25,000Starting from $5,000
Take a validated use case to production — with the guardrails, testing, documentation and handover that a real deployment needs.
Includes
Systems running for real teams, and the code we've opened up.
A short call and a written system design: what repeats, what it costs you, and whether automation is the right answer.
A sprint that ends in something you can use on real data, not slides.
Logging, retries, monitoring and documentation, so your team can own it. Support when you need it.
What we learn building agents and automation, written up as we go.
What we learn building AI agents and automation, from real projects. Unsubscribe in one click.
Avnish Yadav, founder: the engineer you'll work with.
A 15-minute call is enough to tell whether it should be automated, turned into a product, or not built at all.