Spine is a visual workspace for managing and deploying swarms of AI agents that can complete complex tasks from start to finish. Agents can browse the web, conduct deep research, build 50-page strategy documents, generate detailed presentations, create interactive prototypes, and more — with one single prompt.
This is the 4th launch from Spine. View more
Spine Swarm
Launching today
With Spine, you can manage and deploy swarms of AI agents that complete complex tasks from start to finish. Agents browse the web, conduct deep research, build 50-page strategy documents, generate detailed presentations, create interactive prototypes, and more — all with one prompt. The result: Auditable work on a visual canvas that’s far more thorough, accurate, and complete than what you get from ChatGPT, Gemini, or Claude.
Free Options
Launch Team / Built With
Spine
Hey Product Hunt 👋,
Ashwin here, co-founder of Spine.
Spine lets you manage a team of AI agents that work together to complete complex tasks: researching, analyzing, and building full deliverables like apps, landing pages, documents, spreadsheets, presentations. All on one visual canvas you can watch in real time.
Instead of one model doing everything, Spine spins up specialized agents in parallel, picking from 300+ models to use the best one for each step. The result is finished deliverables — not a chat response.
A good first task: "Research [your industry] and create a competitive analysis with a market map, executive summary, and strategic recommendations."
You'll see multiple AI agents spin up simultaneously, browsing the web, structuring data, assembling deliverables. For large projects it can run autonomously for 80+ minutes.
It's free to get started, just signup, no terminal or installation needed. Excited to see what you build 🚀.
Drop your results in the comments — we're reading everything today.
@ashwin_raman Hi Ashwin. How do you manage the balance between giving agents autonomy and ensuring they remain aligned with the user’s goals?
Spine
Hey 👋, Akshay here, co-founder of Spine.
If you've seen what OpenClaw and Claude Code can do for developers — autonomous agents running for hours, finishing real work — Spine brings that same power to everyone. No terminal, no setup. You describe what you need, and a team of agents executes it on a visual canvas.
We just scored 87.6% on Google DeepMind's DeepSearchQA (this measures how well AI answers complex research questions) — ahead of Perplexity (79.5%), Claude Opus 4.5 (76.1%), GPT-5.2 (71.3%), and OpenAI Deep Research (44.2%). We're 8 people. Turns out the right team of agents, drawn from 300+ models, working together on a canvas beats any single model working alone.
Some tasks worth trying:
→ Ask it to audit your website and produce a growth roadmap with a full slide deck.
→ Preparing for a fundraise? Give it your company details and get back a pitch deck, competitive landscape with market sizing, a financial model, and personalized outreach emails for target investors.
→ Describe a product idea and get back multiple interactive prototypes and landing pages exploring different design directions, alongside a PRD and go-to-market strategy.
Everything Spine builds — docs, spreadsheets, decks, prototypes, landing pages — is downloadable and hosted at a shareable link. Just send your team the URL.
Product Hunt exclusive: use code PHLAUNCH10 for 10% off any paid plan.
Would love to hear what the community builds with it!
Interesting architecture. Orchestrating multiple specialized agents across 300+ models to decompose long running tasks into structured outputs on a shared canvas is a strong systems design choice.
Curious how you handle task routing, intermediate state management, and verification of outputs between agents to maintain consistency.
Spine
@sriharsha_karamchati1 Thanks!
The simplified answer is (you can find the thorough answer in this blog post here):
There is a central task agent that breaks down the task into subtasks and spins up specialized persona agents to work on them.
Most of the state is stored on the canvas in different blocks which the agents can review and continue working on.
The agents leave behind structured hand-off notes which informs other agents on how to verify and use the work done by other agents.
Canvas over chat - that just makes more sense for real work. When I'm jumping between research, code, and product decisions, linear chat loses context fast. Love the branching idea. Quick question - can you connect outputs between blocks automatically or is it all manual?
Spine
@ben_gend You can using the chat. The chat spins up agents that connects the blocks for you automatically.
Told
Curious how the swarm coordination actually works when agents hit conflicting conclusions mid-task — like if one agent's research contradicts another's during a 50-page strategy doc. That's where these multi-agent setups tend to fall apart in my experience. The visual canvas angle is smart though, auditability is genuinely the missing piece in most AI workflows right now. Most people don't trust the output because they can't see how it got there.
Spine
@jscanzi Typically the agents present both sides or look for additional information in scenarios of conflict. In my experience cases the resolution depends on the sources that the conflicts were derived from.
We make sure our agents cite all their sources in all the work so both agents and users can audit and decide how they want to resolve these scenarios.
Told
@ashwin_raman Thanks for your reply!
Spine
Let's go!! 🚀 I used Spine with a client the other day who gave me a disjointed mess of documents and links and said "design me a website that's like these!"
I fed everything into Spine before bed and woke up with mockups, a comprehensive design guide, full decision making process, and a report I could hand the client as to the direction I was going & the next steps. And... it did better than I ever could.
1 day of work saved thanks to Spine 💪
Spine
Working on Spine made me realise how different things get once you move from one model to many agents. A lot of the engineering ends up being orchestration routing tasks across models, coordinating long-running jobs, and keeping outputs structured so other agents can build on them.
It’s interesting watching it break down larger tasks and assemble real outputs research reports, strategy docs, prototypes, landing pages, and slide decks.
I’ve also been using it for engineering workflows like researching systems, summarising docs and blogs for quick reads, getting perspectives from multiple agents with different personas, generating quick prototypes, and thinking through edge cases.
Would love to see people try workflows like this too.
Pretty fun system to build and work on.