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Build AI workflows in Python.

company = aisle.inputs.get("company")
 
deal = aisle.integrations.pipedrive.search_deals(
    org_name=company,
)[0]
 
news = aisle.ai.gemini_google_search(
    f"{company} news since {aisle.run.last_run_at}"
)
 
notes = aisle.memories.search(
    company,
    folder="crm-notes",
    limit=5,
)
 
brief = aisle.ai.run_prompt(
    slug="account-brief",
    deal=deal,
    news=news,
    notes=notes,
)
 
aisle.create_chat("Account brief", brief)
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Made for developers.

Everything around your code is handled. You write the logic, and Aisle runs the rest.

  • Auto-deploys to a managed runtime

    Press save and your implementation is online. Every LLM binding and integration is already wired in. No deploy step, no servers.

  • Revisions

    Git-style revisions on every save. Follow each change and roll back in a click.

  • Durable and accountable

    A durable architecture with retries, logging, and a full audit trail. Checkpoints remember your place in a long-running flow.

  • Cache

    Cache information between runs so repeated work stays fast.

  • Files

    Build, create, manage, upload, and distribute files to users. All inline and easy.

Trigger a task from anywhere.

Run on demand, on a schedule, on an HTTP request, or in response to an event from any connected integration.

Manual / On-demand
Schedule
API
Webhook
Bugsnag
GitHub
Gmail
Google News
Jira
Microsoft Teams
Outlook Mail
SERP
Slack
Telegram
See all integrations

Easy to share with your non-programmer team.

Output a chat

Return a read-only or interactive chat, seeded with knowledge and a first message so the recipient can dig in and ask follow-ups.

Share with anyone

Share the task or its chat with specific people or your whole organization. They never touch the script.

Account briefshared · Sales team
Aisle

Acme is at high risk this quarter. Three billing tickets moved to Priority 1 in the last month and churn was flagged at the April QBR.

Sarah

What does CS need to do this week?

Aisle
Ask a follow-up…
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Easier to maintain than a node graph.

A canvas is hard to manage. Changes are onerous and tough to follow. A task moves the problem into code, where logic is easier to reason about, faster to modify, and version tracking is fast and simple.

account-brief.workflow
The account-brief workflow on the Aisle canvas: chat trigger, search deals, set variable, collection loop with summarize tickets and create message, plus a template, X search, condition, and add-to-array sub-branch.
account-brief.py
# Find every open deal at this company.
company = aisle.inputs.get("company")
deals = aisle.integrations.pipedrive.search_deals(
    org_name=company,
)

# For each deal, grab news since the last run.
research = []
for deal in deals:
    news = aisle.ai.gemini_google_search(
        f"{company} news since {aisle.run.last_run_at}"
    )
    if news:
        research.append({"deal": deal, "news": news})

# Hand the lot to a saved prompt to write the brief.
brief = aisle.ai.run_prompt(
    slug="account-brief",
    research=research,
)

aisle.integrations.slack.send_message(
    channel="#revenue",
    text=brief,
)

Write your first task in the editor.

Free plan includes the runtime, integrations, and revision history.

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Tasks share state, prompts, and memory with the other building blocks. Reach for the shape that fits.

Projects

A shared home for a team or domain. Tasks live in a project alongside its prompts, memories, and connectors.

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Memories

Search and store knowledge from inside a task with a single call. No vector database to provision.

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Reusable Prompts

Saved prompts a task calls by slug. Edit the prompt and every task that references it updates with it.

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Write your first task.

Open the editor, write a script, and run it against your connected accounts.

Start building
Read the SDK docs.