Startups
Automate the first painful workflows quickly, so the team spends less time on repetitive operations from day one
Current automation + AI packages
Fixed packages for first workflows, AI assistants, integrations, and operational automation with a clear launch scope.
AUTOMATION
Mini Automation
Ideal for: removing recurring manual work
$199
Timeline depends on scope
Included
- 1 workflow (1 trigger → 1 outcome)
- 1 integration (Gmail / Sheets / Slack / CRM, etc.)
- Basic error handling (fail + notify)
Best fit for first workflows
AUTOMATION
Automation Sprint
Ideal for: saving 2–3 processes per week
$399
Timeline depends on scope
Included
- Up to 3 workflows
- Up to 2 integrations
- Retry logic + notifications
- Daily email report or simple logs
AUTOMATION
Ops Automation
Ideal for: daily/weekly jobs with oversight
$699
Timeline depends on scope
Included
- Up to 6 workflows
- Up to 3 integrations
- Structured logs + retry/queue basics
- Basic admin controls (start/stop/run)
AI WORKFLOW
AI Assistant Lite
Ideal for: inbox / summarization / extraction
$499
Timeline depends on scope
Included
- 1 AI use case (summary / classify / extract / draft)
- 1 source (docs / emails / tickets / forms)
- Output to 1 destination (Slack / email / CRM)
- Prompt + guardrails
AI WORKFLOW
AI Workflow
Ideal for: combining AI + automation
$899
Timeline depends on scope
Included
- 2 AI use cases + automation around it
- 2 sources + 2 destinations
- Guardrails + fallbacks (fail-safe path)
- Notifications + basic logging
Send a short note about which process is manual today, what tools are involved, and where AI is needed. We'll suggest the shortest path to a working scenario.Quick estimate →
From bottleneck to working scenario
Four steps so the automation does not stay stuck at idea level.
Process map
Identify where time is lost, who is involved, and which triggers, exceptions, and manual checks exist today.
Scenario design
Shape a practical automation or AI use case with guardrails, fallback behavior, and launch rules.
Integration and testing
Connect services and validate real data, edge cases, notifications, and failure behavior.
Launch and handoff
Ship the scenario with instructions, baseline monitoring, and clear operating control points.
Short and honest
The main questions before the first launch.
Do you only build AI, or regular automation too?+
Both. In many cases the best result comes from combining automation, AI, and a clear fallback path instead of forcing pure AI into the workflow.
Can this connect to our existing tools?+
Yes, if the tools expose APIs, webhooks, email flows, forms, or other clear integration points. That is usually where scoping starts.
How do you reduce AI mistakes?+
Through guardrails, narrow task scope, notifications, human review where needed, and a fail-safe path when the model is not confident.
Can we start with one small scenario?+
Yes. That is exactly what the smaller packages are for: remove one concrete bottleneck first and then expand from there.
