Workflows that run themselves
Replace manual handoffs with intelligent automation. Emails trigger tickets, approvals happen in Slack, exceptions get flagged before they become problems.
30-min call. We map your process and tell you what should be automated, what needs human review, and what should stay manual.
Workflows we connect and automate
We work with the tools you already use and add AI where simple rules are not enough to handle the variation.
Email to action
Incoming emails are classified by intent, data is extracted, tickets are created, and CRM records are updated before anyone reads the message. The inbox stops being a manual to-do list. Works with Gmail, Outlook, and custom inboxes.
- Classified by intent, data extracted before anyone reads - the inbox stops being a manual to-do list for your team
- Tickets, CRM records, tasks created automatically - right system updated within seconds of email arrival
- Works with Gmail, Outlook, and custom inboxes - no change to how people send, no inbox restructuring required
- Human review queue for uncertain classification - system flags what it is not sure about rather than guessing
Approval workflows
Purchase requests, content sign-offs, leave approvals, contract reviews. Smart routing based on amount, department, or risk level. Reminders sent automatically. No more chasing people on Slack to get a decision.
- Purchase requests, sign-offs, leave, contract reviews - any approval with defined rules can be automated
- Smart routing by amount, department, risk level - small expenses can be auto-approved, while larger ones go to the CFO automatically
- Reminders sent automatically to approvers - no more Slack messages asking where the approval is
- Full audit trail of every decision - who approved, when, and with what data, all logged for compliance
Alerts and escalations
Monitors thresholds across data sources and routes alerts to the right person via Slack, email, or SMS. Configurable severity levels, on-call schedules, and escalation chains. The right person hears about problems, not everyone.
- Threshold monitoring across multiple data sources - API responses, database metrics, external feeds, log events
- On-call schedules and escalation chains - right person gets the alert, not everyone on the team
- Slack, email, or SMS delivery - channel configured per alert type and severity level
- Configurable severity and suppression rules - avoid alert fatigue by filtering noise at the source
Cross-tool sync
Keeps HubSpot, Jira, Notion, and your internal systems consistent without manual copying between tabs. Bidirectional where APIs allow it, with clear conflict rules when both sides change.
- HubSpot, Jira, Notion, and custom internal systems - any combination connected via API
- Bidirectional where APIs allow it - real-time or scheduled sync depending on API limits and access
- Conflict resolution when both sides change - defined rules for which system wins on simultaneous edits
- No manual tab-switching or CSV exports - data stays aligned across tools, with sync errors logged instead of hidden
Onboarding sequences
A new customer or employee triggers account setup, welcome emails, task assignment, and access provisioning in one event. Multiple systems updated in the right order, with retry logic if any step fails.
- Account setup, welcome emails, access provisioning - one new-user event triggers actions across multiple systems
- Multiple systems updated in correct order - Slack invite before CRM record, task assigned before project access
- Retry logic on step failures - if one system is down, the queue holds and retries rather than failing silently
- Fully auditable trail of every onboarding step - you can see exactly what ran, when, and what the result was
AI decision nodes
Where fixed rules run out, AI classifies intent, assesses risk, or generates a draft response. A human confirms before anything consequential happens. We design the escalation path before writing any code.
- Classifies intent and assesses risk at scale - handles the variation that fixed rules cannot capture
- Generates draft for human review - AI proposes, human confirms before anything consequential happens
- Escalation path designed before build - we define the failure modes and human-review triggers upfront
- Full decision log for auditability - every AI classification recorded with input data and confidence score
How we design your workflow automation
- 01
Map the current process
Walk us through it step by step. We document every handoff, every decision point, every exception that currently gets handled by someone's tribal knowledge.
- 02
Design the automation
Which steps get automated, which need a human, what the failure modes are. We draw the logic before writing a line of code.
- 03
Build the connectors
Custom integrations to your existing tools via their APIs. For production workflows, we use custom connectors where no-code tools become too fragile.
- 04
Run parallel
The automation runs alongside the manual process until accuracy is confirmed. No big-bang switchover.
- 05
Launch, monitor, and improve
Every automated action is traceable. After launch, we monitor failures, retries, and edge cases so the workflow can be adjusted as your process or tools change.
Common questions
What tools can you integrate?
Most API-first tools with stable API access or webhooks. Common ones: HubSpot, Salesforce, Slack, Jira, Notion, Monday.com, Google Workspace, Microsoft 365, and custom internal systems.
How is this different from Zapier or Make?
Zapier works for simple linear flows. We build systems that handle ambiguity, classify inputs, manage exceptions, know when to escalate to a human. The reliability bar is different.
What if an automated step fails?
Every automation we build has error handling and fallback paths. Failed steps get logged, someone gets notified, and the item goes to a manual queue. Nothing disappears silently.
Can existing Zapier flows be migrated?
Yes. We audit them, identify where they break down or have hidden fragility, and rebuild as proper custom pipelines.
How long until we see ROI?
Most clients measure time savings within the first month. We baseline the manual effort before we start so the comparison is concrete.
How much does AI workflow automation cost?
A short workflow scope check can start from €1,000–5,000. A focused proof of concept usually ranges from €3,000–15,000. A first production workflow with integrations, routing logic, retries, audit logs, and human-review queues usually starts from €7,000–30,000. More complex workflows are estimated after we review your tools, edge cases, data access, and security needs.
Do we always need AI for workflow automation?
No. Many workflows are better solved with rule-based logic, API integrations, or scheduled jobs. We use AI when the workflow involves unstructured text, variable inputs, classification, summarization, risk scoring, or decisions where fixed rules become too brittle.
What happens after the workflow goes live?
We monitor failures, retries, edge cases, and user feedback after launch. When APIs change, business rules evolve, or new exception cases appear, we adjust the workflow logic, connectors, alerts, and approval paths.
You might also need
AI automation
The broader picture: document processing, email routing, approvals, and cross-system automation.
Document AI
Automate the data extraction step that feeds your workflows.
AI chatbots
Add a conversational interface to trigger and check on your automated workflows.
Which workflow still depends on manual handoffs?
Describe it in plain language. We will tell you what can be automated, what needs human review, and what should stay manual.
Map your workflow →