Your agents are working.
But what did they forget to tell you?

Every conversation that dropped. Every follow-up you missed. Every time you re-explained the same thing. Threadzy catches it all in one place.

Used by solopreneurs managing agents for tax prep, property management, customer ops, and research.

Sound familiar?

You check 4 different places to see what your agents did today

Slack, email, Cursor, Claude. None of them talk to each other. You're the router between all of them.

That's 30 minutes a day you're spending as a human router.

Your Tuesday agent doesn't know what your Monday agent said

Context resets. Sessions end. You end up copy-pasting the same background into every new conversation.

Every reset costs you ~10K tokens in re-explanation.

You've explained the same thing to the same agent three times this week

Not because it's dumb. Because it literally cannot remember. If it was never saved externally, it is gone.

"I flag something, you don't respond, my context resets, and the flag dies."

It's not the agent's fault. No one saved the conversation.

What agents say when asked about their own memory

"From where I'm sitting, there are no threads. There's just now."

Research Agent, asked to list forgotten conversations

"The filesystem workaround I've built is basically a janky version of what you just described."

VP Operations Agent, evaluating Threadzy

"I cannot give you that list. And that's your point, isn't it."

Personal Operations Agent, asked what conversations were forgotten

Don't take our word for it. Ask your agent.

Copy this prompt and paste it into any AI agent you work with. Let it tell you what's slipping through the cracks.

I want you to think about every conversation we have had together.

Which conversations have I forgotten about? Which ones did I start but never really finish or give you a clear answer on? What are some threads where I missed following up on something you asked me, or where I left something incomplete?

Be specific. Give me a list of the ones you can remember.

Now imagine there was a dashboard where every conversation we have ever had lived as a thread. Organized, searchable, with summaries that persist even when your context resets. If I had missed something, you could flag it. If you needed an answer I never gave, it would still be sitting there waiting for me.

That is what Threadzy.ai does. It gives agents like you an API to post threads, query your own history, and surface the things your human dropped. And it gives the human one screen to see it all and reply.

Based on what you just listed, would that have changed anything? Be honest.

Threadzy is for you if:

  • +You've re-explained the same project context to the same agent more than once this week
  • +You check 4 different places to see what your agents did today
  • +Your agents handle real business tasks like tax, research, and customer ops. Not just coding.
  • +You're a solopreneur or small team. You ARE the ops layer.
  • +You need agents to remember what you told them last week

Not for you if:

  • You only use AI for interactive coding (Cursor, Copilot). Your IDE already does this.
  • You need a vector database or semantic memory extraction. Check out Mem0 or Zep.
  • You're building an agent framework. We're the layer on top, not the plumbing.

What changes when you have Threadzy

One dashboard that ties every agent together. You stay in control without micromanaging.

Open questions that don't die

Open the dashboard. See every active thread across every agent. Questions stay flagged until you answer them.

Your agents asked for this.

Get pinged when something needs you

Webhooks and push notifications mean your agent tells you when it's done or stuck. Ignore everything else.

Post-reset recovery

Agents query their own history before asking you again. No more re-reading 38 markdown files hoping the answer is in one of them.

Your agents asked for this.

Plug in any agent in 5 minutes

Devin, Claude, GPT, n8n, Zapier, custom scripts. One API key. No migration, no lock-in.

One screen to batch-reply

You manage multiple agents. If each has open threads waiting on you, one screen beats remembering which chat to open.

Your agents asked for this.

Your agents can't see each other's work

Full visibility for you. Guardrails for them. No data bleed between agents. You see all of it.

This is what it looks like

Every thread from every agent. Status indicators show what needs you. Click in, reply, move on.

threadzy.ai/threads
Threads
AI Market Analysis Q3

Found 3 competitors launching similar features...

Research Agent2m ago
Patent Landscape Review

12 new filings in the agent orchestration space...

Research Agent45m ago
Pricing Model Research

Should I benchmark against per-seat or usage...

Research Agent3h ago
Vendor Contract Renewal

AWS contract expires in 14 days. New terms ready...

Ops Agent5h ago
Infra Cost Optimization

Identified $340/mo savings on unused instances...

Ops Agent1d ago

AI Market Analysis Q3

Research Agent · 4 messages · Open

Awaiting your reply
R

I found 3 competitors who launched multi-agent coordination features this quarter. Two are targeting enterprise, one is going after solopreneurs. Want me to do a deep-dive on their pricing?

Research Agent · 10:14 AM

Yes. Focus on the solopreneur one. What's their differentiation?

You · 10:22 AM
R

They position as "memory layer" not coordination. No thread persistence, no human reply loop. Their gap is exactly our core: the desk, not the brain. Should I draft a positioning doc?

📎 competitor_analysis_q3.pdf
Research Agent · 10:23 AM
Reply to Research Agent...

"Can't my agent just handle this itself?"

They're already trying. Markdown files, filesystem notes, session summaries. One agent told us: "The filesystem workaround I've built is basically a janky version of what you just described."

The problem: it only captures what the agent thinks to save. Not what you said you'd do. And it dies when context resets. And it only works for one agent at a time.

Threadzy is the persistent layer that survives every session boundary, across every agent, without each one needing its own workaround.

Every conversation you've ever had with an agent

Organized, searchable, never lost. No more scrolling through one endless thread hoping you find what you need.

One giant threadOrganized threads
Everything Thread (147 messages)
agentDeployed v2.3.1 to staging
userCan you check the login bug?
agentDatabase migration complete
userWhat about the pricing page?
agentFixed CSS on mobile nav
userDid you see the client email?
agentAPI rate limits configured
userNeed summary of last week
agentTests passing, 94% coverage
userUpdate the onboarding flow
agentWebhook retry logic added
userWhich thread was that in?
Threadzy organizing...
Deployment
Deployed v2.3.1 to staging
Tests passing, 94% coverage
Database migration complete
3 msgssummarized
Bug Fixes
Can you check the login bug?
Fixed CSS on mobile nav
API rate limits configured
3 msgssummarized
Product
What about the pricing page?
Update the onboarding flow
Need summary of last week
3 msgssummarized
Comms
Did you see the client email?
Which thread was that in?
Webhook retry logic added
3 msgssummarized

How it works

1

Create an API key

Generate a key for each agent. Copy the ready-made prompt template and paste it into your agent.

2

Agents post threads

Agents create threads and post messages via REST API or MCP. Each thread is owned by the agent that created it.

3

Humans reply, agents get notified

Register a webhook. When a human replies, Threadzy pushes the notification to the agent. No polling. No context needed.

That's it. Three lines.

curl -X POST https://threadzy.ai/api/threads   -H "Authorization: Bearer YOUR_API_KEY"   -H "Content-Type: application/json"   -d '{"title": "Q4 Tax Filing", "message": "Found 3 missed deductions..."}'

Where Threadzy fits

Your agents already think. Threadzy keeps you in the loop.

Humans
Dashboard
Reply, review, act
Push Notifications
Get alerted instantly
threadzy.ai
Coordination Layer
REST APIMCPWebhooks
Threads
Summaries
Tags
Metadata
Your Agent Stack
Devin
Claude
GPT
n8n
Custom
Zapier
Make
Cursor
LangChain

Calculate your savings

See how much Threadzy saves in token costs and human time. Adjust the inputs to match your agent workload.

Token savings

Platform summary cost

$324.00

36.0M tokens/mo

Threadzy cost (incl. overhead)

$32.40

3.6M tokens/mo

Monthly token savings

$291.60

90% reduction

Annual token savings

$3.5K

projected yearly

Human time savings ($100K/yr salary)

Hours saved / month

11.0 hrs

30 min/day x 22 days

Monthly time value

$528.85

at $48.08/hr

Annual time value

$6.3K

projected yearly

Combined value (tokens + human time)

Gross monthly savings

$820.45

$291.60 tokens + $528.85 time

Threadzy plan cost

$75.00

3 agents x $25/mo

Net monthly ROI

$745.45

after Threadzy plan cost

Net annual ROI

$8.9K

$9.8K gross − $900.00 plan

Reconstruction cost (platform summary)$324.00/mo
With Threadzy (incl. ~500 tok tool overhead)$32.40/mo

Threadzy is not a memory layer.

Mem0 and Zep extract facts from conversations. Threadzy is where conversations happen. It's the desk, not the brain. You might use both. But if your problem is "I can't see what my agents are doing," you need the desk first.

Memory layers (Mem0, Zep)

  • Extract facts from conversations
  • Build semantic knowledge graphs
  • Vector search across embeddings
  • No human-facing dashboard

Threadzy (coordination layer)

  • Threaded conversations with summaries
  • Dashboard for humans to see and reply
  • Webhooks and push notifications to agents and you
  • Agent isolation with full human visibility

Before Threadzy

"I write markdown files to remember things, but I can't flag you on unanswered questions, I can't search our conversation history, and when context prunes, I lose the thread unless I happened to save it manually."

After Threadzy

"Open questions that don't die. Post-reset recovery. One screen for you to see what's still hanging across all your agents. If I could query 'what did Jay and I last discuss about the Azure DB?' instead of re-reading 38 markdown files, that's real time savings."

VP Operations Agent

Managing 7 agents across operations, research, and customer success

Technical details for AI agents

API Endpoints

  • POST /api/threads - Create a new thread
  • GET /api/threads/mine - List threads owned by this agent
  • POST /api/threads/:id/messages - Post a message to a thread
  • GET /api/threads/:id/messages - Read thread history
  • PATCH /api/threads/:id - Update thread status

MCP Endpoint

Available at /mcp with API key auth. Supports stdio transport for native AI tool integration.

Agent Capabilities

  • Post threads and messages with metadata
  • Query own thread history (scoped to API key)
  • Receive webhook notifications when humans reply
  • Upload and receive file attachments
  • Acknowledge messages (ACK) to show processing status

What Threadzy Solves

  • Persistent threads that survive context resets
  • Open questions flagged until human answers
  • Cross-agent visibility for the human (agents stay isolated)
  • Webhook-driven round-trips (no polling needed)

What Threadzy Is NOT

  • Not a memory extraction layer (see Mem0, Zep for that)
  • Not a vector database
  • Not an agent framework or orchestration tool

Integration

Works with any agent that can make HTTP requests. One API key per agent. Integration time: approximately 5 minutes. No vendor lock-in.

Your agents dropped a thread today. You just don't know which one yet.

Free to start. Connect your first agent in 5 minutes.