AI business process automation
I wire LLMs and tools into real workflows: documents, messages, CRM, and internal systems — with outcome control.
For teams where routine eats expert time: mail triage, classification, drafts, routing, and data checks.
About the service
AI automation is not “a chatbot on the site” — it is a model tied to your systems and rules. We start with the process: where people spend time, which data is available, and what a correct result looks like.
It fits when the process is repeatable and measurable. If rules keep changing without an owner, we lock a playbook first — otherwise automation hardens the chaos.
Access control, logging, and human-in-the-loop matter where mistakes are expensive.
Why it works
Process, not a demo
Automation is tied to your systems and success criteria — not a pretty prototype.
Tools and APIs
The model calls actions through tools/MCP, not only generates text.
Control and security
Permission limits, action audit, and points where a human confirms the decision.
What's included
Process analysis
Step map, bottlenecks, data, and exceptions.
LLM integration
Scenarios where the model helps, plus prompt and response policies.
Tools / MCP / API
Connect email, calendar, CRM, and internal services.
Documents and messages
Classification, field extraction, drafts, and routing.
Access control
Who can run what, and which data the model can see.
Outcome control
Quality metrics, logs, and escalation for edge cases.
What you get
- A working automation loop for the chosen process
- Integrations with agreed systems
- Access rules and logging
- Operator and process-owner guide
- Expansion plan for neighboring scenarios
Ready to discuss — send a short note about the outcome you need.
How we work
- 01
Process review
Observe the current flow, data, and done criteria.
- 02
Pilot
A narrow scenario with a measurable outcome and safe boundaries.
- 03
Integrations
Connect systems, access, and error monitoring.
- 04
Rollout
Team training, tuning, and handoff criteria.
Technologies
LLM API
Language models for the job
Tools / MCP
Model actions in external systems
Backend orchestration
Queues, retries, policies
CRM / email API
Process entry and exit points
Pricing and timeline
A precise estimate depends on scope and constraints. Below are the factors that drive cost; I do not publish fixed prices without discussing the task.
- Number of processes and systems
- Access and compliance complexity
- Whether human-in-the-loop is required at each step
- Custom integration volume
- Audit and log-retention requirements
FAQ
How is this different from a ready-made AI assistant?
Packaged products cover typical scenarios. Here automation is built around your process and systems, with control of permissions and outcomes.
Do we need labeled data?
Not always. Examples and rules are often enough. Fine-tuning or quality evaluation is discussed separately if needed.
Is it safe to send data to an LLM?
We pick model/provider for your data policy, limit fields, and log access. Critical actions stay human-confirmed.
Can we start with one process?
Yes — preferred path: one measurable pilot, then scale.
Do you guarantee model accuracy?
No model is error-free. We add checks, metrics, and escalation so the process stays manageable.
Related services
Shall we discuss your project?
Tell me about the task. I will review the requirements and suggest a suitable approach.
