co-founder @UseIrisAgent & @raisi_ai | research collaborator on multi-agent simulations @ Berkeley | AI optimistiris-agent.co San FranciscoJoined March 2024
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Hey, we just went live on @ProductHunt with Iris!
we’re building AI agents for the work that gets stuck between people and apps.
a customer needs an update. engineering is waiting on a decision. someone needs to check the CRM, read the Slack thread and follow up. you end up
We’re live on @producthunt with Iris today.
Context is a big part of what we’re building.
Instead of repeatedly making you explain the same things – the more Iris works inside your company’s workflows, the more context it can carry into the next task.
A few things we care a lot about as we build:
• model agnostic because we want to use the right model for the task, not force everything through one provider
• self-hosted routing for sensitive company data and IP-heavy work
• expensive reasoning where it actually improves the outcome, not on every single task
• a very simple interface with most of the complexity happening underneath
• memory that makes recurring workflows meaningfully better the more you use it
This video shows what that compounding context loop starts to look like ↓
Hey, we just went live on @ProductHunt with Iris!
we’re building AI agents for the work that gets stuck between people and apps.
a customer needs an update. engineering is waiting on a decision. someone needs to check the CRM, read the Slack thread and follow up. you end up
automating a bad workflow is still a bad workflow.
Iris looks for what can be improved inside the workflow, then helps optimize the process itself.
the more integrated Iris becomes in how your company works, the better it gets at improving it.
Hey, we just went live on @ProductHunt with Iris!
we’re building AI agents for the work that gets stuck between people and apps.
a customer needs an update. engineering is waiting on a decision. someone needs to check the CRM, read the Slack thread and follow up. you end up
Hey, we just went live on @ProductHunt with Iris!
we’re building AI agents for the work that gets stuck between people and apps.
a customer needs an update. engineering is waiting on a decision. someone needs to check the CRM, read the Slack thread and follow up. you end up
6/ that’s the loop we’re ultimately building toward.
run the workflow.
keep the useful context.
find repeated friction.
propose a better way to run it.
test the change.
carry what worked into the next run.
the goal isn’t to put AI into as many steps as possible.
it’s more work completed, less coordination, better processes and control over where the company’s information goes.
Iris is live on Product Hunt today:
producthunt.com/products/iherm…
Hey, we just went live on @ProductHunt with Iris!
we’re building AI agents for the work that gets stuck between people and apps.
a customer needs an update. engineering is waiting on a decision. someone needs to check the CRM, read the Slack thread and follow up. you end up coordinating the whole thing yourself.
Iris brings agents into those workflows to help gather the information, prepare the next steps and keep work moving across the tools your company already uses.
there are a few things we care a lot about ↓
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