For businesses drowning in
manual work.

The problem

Your team is the bottleneck. Reports are late.

• Reports that take days to pull
• Spreadsheets sprawled across the org
• Workflows that need a human babysitter
• CRMs full of stale data
• "Ask Sarah" being your single point of failure
• Engineering team booked solid on revenue work

What is an agentic ops system?

Real software with a reasoning layer.

Three things real software does, plus one new thing. Most automation breaks the moment something doesn’t fit the schema. Agents handle the exceptions.

• Reads

  Your data across CRM, ERP, warehouse, SaaS, sheets — wherever it lives.

• Manipulates

  Records, fields, statuses. Triggers downstream workflows. Updates source-of-truth systems.

• Coordinates

  Multi-step processes across systems. Hands work between agents and humans.

• Reasons

  Through ambiguity using LLMs — the "it depends" cases that break Zapier.

What we build

Concrete examples.

• Executive reporting agent

  "Brief me on Q-to-date pipeline by segment, flag anomalies vs. last quarter, Slack me a 5-bullet summary every Monday."

• RevOps workflow agent

  "Watch HubSpot, enrich every new lead, score against ICP, route to the right AE, log activity, notify the team."

• Finance operations agent

  "Pull QuickBooks + Stripe + bank, reconcile, flag anything off, draft the weekly cash report."

• Internal knowledge agent

  "Let our team ask questions across Notion, Slack, and our SOPs in plain English."

• Order operations agent

  "Watch Shopify orders, flag fulfillment risk, open Linear tickets, ping the ops Slack."

How we’re different

Owned code. Real reasoning. Days, not months.

The three packages

Pick a speed.

FAQ

Last-mile objections.

What we ship

Real code. Owned by you.

Every engagement ships to your repo. Typed, tested, documented, with a clean module layout. Below is a representative slice from a recent build.

# agents/exec_brief.py
from ctb import Agent, sources, channels

@Agent.scheduled("0 7 * * *")  # 7am daily
def exec_brief(ctx):
    pipeline = sources.snowflake.query(ctx.sql.weekly_pipeline)
    revenue  = sources.stripe.last_n_days(7)
    deltas   = ctx.compare(pipeline, baseline="trailing_4w")

    flagged  = [d for d in deltas if d.sigma > 2]

    summary = ctx.llm.narrate(
        prompt=ctx.prompts.exec_brief,
        data={"pipeline": pipeline, "revenue": revenue, "flagged": flagged},
    )

    channels.slack.post("#leadership", summary, thread_handlers=[ctx.followup])
    return ctx.log(metric="exec_brief.posted")

Stack agnostic. We ship in the language and infrastructure that fits your team — Python, TypeScript, your cloud.