Launching today
DataDack
AI Agents, Workflow Automation & IoT — Built in India
7 followers
AI Agents, Workflow Automation & IoT — Built in India
7 followers
DataDack is a unified AI + Automation + IoT platform built for production. Unlike fragile no-code tools, it runs on a Go core with <10ms latency, 10k+ RPS, and 99.9% uptime. Deploy persistent RAG-enabled AI agent swarms, visually orchestrate workflows across 100+ integrations (OpenAI, Kafka, Stripe, MQTT), and sync IoT telemetry — all within a localized AI Gateway. India-first, mTLS encrypted. Free to start.
We built DataDack because every enterprise AI project we saw was drowning in glue code — duct-taping LLMs to databases, IoT sensors to APIs, and workflows to each other with fragile scripts.
DataDack is our answer: a unified, production-grade platform built in Go. Deploy autonomous AI agent swarms with persistent RAG memory, visually orchestrate complex workflows across 100+ integrations, and sync IoT telemetry — all within a localized AI Gateway that keeps your data in-region.
We're India-first (AWS Mumbai & Hyderabad), DPDP compliant, with mTLS encryption across every node. Free to start, no credit card needed.
Would love your feedback — what use case would you try first?
When we decided to build DataDack, the first decision was the hardest: don't cut corners on the core. We chose Go not just for performance, but because when you're orchestrating AI agents, IoT streams, and workflow automations simultaneously, you need a runtime that doesn't flinch under pressure. Sub-10ms latency and 10k+ RPS aren't marketing numbers — they're the baseline we engineered to.
The hardest problem we solved? Making persistent RAG memory work reliably across autonomous agent swarms without state collisions. Most platforms fake this with stateless wrappers. We built it into the core.
We also obsessed over the developer experience — the visual workflow builder talks directly to the same engine that powers the API, so what you build visually is exactly what runs in production. No translation layer, no surprises.
If you're a developer who's tired of stitching together LangChain + n8n + custom glue code and praying it holds in prod - DataDack was built specifically for you.
Drop any technical questions below 👇