End-to-end business process automation: from request to result with no manual steps
End-to-end business process automation for companies where every request passes through several people and systems. We map the process, remove manual steps, connect the systems and add monitoring so failures are visible at once.
What hurts
A customer request passes through three people and four systems. Each one retypes data and waits for the previous step. Nobody can see where it is stuck.
Staff spend hours copying between CRM, ERP and spreadsheets. When someone is on holiday, the process stops. Customers are the ones who find the errors.
Some scripts and no-code flows already exist, but different people built them. They break without warning and nobody knows how they work. Scaling them feels risky.
What we build
- Discovery: current and target process map, count of manual steps
- Orchestration on Temporal or n8n with retries and timeouts
- Integrations with CRM, ERP such as SAP or Odoo, carriers, email and spreadsheets
- AI steps for parsing text, classification and draft replies
- Exception queue for people with the reason explained
- Run log and failure monitoring with alerts to Telegram or email
- Roles and permissions for staff
- Staged launch: part of the requests first, then the full flow
What you get
- Automated process running in production
- Process diagram and technical documentation
- Source code, access and deployment guide
- Dashboard with volume, cycle time and exceptions
- Training for process owners
How we measure the result
- Cycle time from request to result
- Number of manual steps in the process
- Share of requests completed with no human touch
- Failures and time to fix
Systems and stack
Industries
Questions
How much does process automation cost?
From $5,000. The price depends on the number of steps, systems to integrate, API availability and how many steps need AI. After a 1–2 week discovery we give a fixed estimate within 2–3 days.
Where do we start if we have many processes?
With the one that repeats most and hurts most. During discovery we count manual steps and time so the choice is based on numbers. Other processes follow in later phases.
Why Temporal instead of simple scripts?
Temporal keeps the state of every run, retries failed steps and shows exactly where a process stopped. For simple flows n8n is enough. We explain the choice during discovery based on load and criticality.
What if a system has no API?
Then we use file exchange, a direct database connection or an RPA bot that works in the user interface. A typical case is an old warehouse system that only exports stock as a scheduled file. These steps are more fragile, so they get extra monitoring.
How do you guarantee the result?
The success metric is written into the contract. We launch on part of the requests first and compare with manual work. If we exceed the estimate through our fault, we finish at our own cost. After launch we offer SLA support.
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