Information gets copied
Email, CRM and filing contain the same details in different versions.
AI Automation · Peak Atlas
Your team should look after customers. Not transfer the same data three times.
We build automations for recurring workflows in sales and operations. A defined pilot shows whether your team actually saves time after review, rework and operation.
- Check existing systems first.
- Measurably improve one specific workflow.
Bring a recurring task. In the initial consultation, we'll clarify the effort, the data and a sensible next step.
Process mapping · Pilot with review points · documented handover
The work between systems
The software is there. Your team still handles the handovers.
Reading requests, transferring information, finding who's responsible, updating notes: many small tasks add up to a recurring effort.
Tasks are waiting to be assigned
Someone first has to decide who is responsible and what information is missing.
Drafts always need the same start
Employees repeatedly gather the same data before the actual work begins.
We look for the clearly defined step whose improvement is noticeable and verifiable in everyday work.
One workflow instead of an abstract AI promise
A request becomes a next step you can verify.
If an important detail is missing or the case is unclear, it goes to the responsible person with a note. The workflow has to cope with the difficult inputs too.
Illustrative pilot example · no customer data and no claimed time savings
Before
- A traceable decision on where the next euro goes.
- It assigns the request and transfers the details to the CRM.
- It creates a task and prepares a reply.
In the pilot
- The automation structures the information at hand and suggests an assignment.
- Missing or contradictory information is flagged.
- A person reviews the draft and approves saving or sending.
Whether it pays off for you, we measure including human review and any necessary rework.
How we assess the benefit
Prove one workflow first. Then decide on the rollout.
We start with process and data. Then we choose the right combination of rules, interfaces and AI.
- 01
Measure the starting point
Capture the frequency, processing time and typical errors of the current workflow.
- 02
Define the pilot
Define inputs, expected outputs, permissions and approval points.
- 03
Test edge cases
Check incomplete data, contradictions and edge cases, and document the results.
- 04
Decide on operations
Assess benefits, remaining work, running costs and responsibilities together.
Evaluation: time per case including review, errors and rework, plus the cost of use and maintenance. Only the full picture shows the relief.
What you get
A usable workflow takes more than one working demo moment.
Other possible use cases include structured CRM notes, internal knowledge search with sources and document pre-checks. We choose based on the task and the data.
Process mapping and selection
A documented workflow and a reasoned assessment of suitable use cases.
Pilot and test log
A defined use case with specified inputs and outputs, review points and results from edge-case testing.
Handover and operating concept
Responsibilities, error handling, maintenance and a traceable decision on regular operation.
- 01
Put it in context
Understand the task and the existing effort together.
- 02
Agree
Document pilot scope, access, costs and review criteria.
- 03
Hand over
Evaluate results and agree on operation or adjustment.
When automation makes sense
The task repeats. A good result can be described.
- A workflow comes up regularly and noticeably costs your team time.
- The required information is available or can be organized.
- A responsible person can review results and support the pilot.
If the process itself is constantly unclear or no one can describe a good result, we organize the workflow first. Otherwise automation is hard to verify too.
For the pilot examples described, approval stays with a person. Which routine may later run automatically is determined by purpose, permissions and error risk.
Organize data and handovers: CRM optimization
As seen in
Before you decide
What your team should know before a pilot.
Do we have to buy new systems?
We first look at the CRM, email and filing you already have. We only suggest additional tools if the specific use case calls for them.
What does a pilot cost?
That depends on the workflow, interfaces, data and test scope. We define the scope up front and separate setup costs from later costs for use and maintenance.
What data do you need?
Only the data required for the agreed workflow. Purpose, access, processing and responsibilities are clarified with you and documented before implementation.
What happens with errors or missing information?
In the pilot, we define recognizable exceptions, review notes and the handover to a responsible person. The tests show where the workflow is reliable and where more safeguards are needed.
Can the AI send messages on its own?
In the pilot described, a draft is reviewed by a person before sending. Whether a clearly defined routine case may later trigger automatically is decided based on purpose, permissions, error risk and documented approval rules.
Who maintains the automation?
We settle this before regular operation. We discuss which tasks your team takes on and whether ongoing support from us is part of the agreed scope.
What if the pilot isn't worth it?
Then we document the result and decide whether to adjust or stop. A pilot is meant to enable exactly that decision before you invest in a broad rollout.
Your next step
Which task would you like to take off your team's plate?
Describe a workflow that comes back every week. We'll clarify where the effort comes from, what data is available and whether it could become a worthwhile pilot.
- Which task, and how often?
- Which systems and information are involved?
- How would you recognize real relief?
For the initial consultation, a description and an anonymized example are enough. Confidential customer data isn't needed.
