OpenClaw Consulting

Find the workflow worth fixing. Then build the system around it.

OpenClaw Consulting helps founder-led businesses turn messy follow-up, scattered context, and recurring admin into practical AI-assisted workflows — starting with a €99 diagnosis when the first fix is not obvious.

Clear problem already? request scope. Need the broader consulting page? See AI workflow consulting. Need trust first? See anonymized proof examples.

Commercial spine

Audit path

Unclear bottleneck → €99 diagnosis → first workflow decision

Implementation path

Clear bottleneck → scoped build → human-approved workflow in daily use

Timo Möbes
Former Doctolib AI Champion 7+ years enterprise consulting 91 NPS score Cyprus-based, remote-first

The platform

What is OpenClaw?

OpenClaw is an open-source AI agent platform that can work across chat, email, browser sessions, files, APIs, and internal tools. It is not just another chatbot. Configured properly, it becomes an operating layer for research, follow-up, CRM updates, reporting, and recurring workflows — with human approval where judgment matters.

  • Multi-channel control: Telegram, WhatsApp, Slack, Discord, web
  • Tool integrations: email, calendar, CRM, Airtable, Google Workspace, APIs
  • Workflow automation: research, follow-up, reporting, CRM updates
  • Human approval: drafts, checkpoints, and safe escalation rules
  • Production deployment: VPS/Mac mini, security, memory, monitoring
  • Scheduled operations: cron jobs, heartbeat checks, recurring tasks

OpenClaw maintenance / reliability support

Keep your AI workflows working after launch

Once an AI workflow becomes part of daily operations, the real risk is not the first build — it is what happens when WhatsApp stops responding, a cron job fails, a model gets rate-limited, a plugin changes, or a saved workflow no longer produces the expected result.

OpenClaw helps restore, validate, and stabilize operational AI workflows so teams know what is working, what is only partially restored, and what needs manual proof before it is scheduled again.

Reliability sequence

Restore first. Validate second. Schedule last.

When a scheduled workflow fails, OpenClaw does not treat a simple chat response as proof that the automation is fixed. The safe sequence is: restore the interface, run the saved workflow manually, verify the real output, then recreate the schedule only after the manual result is correct.

Support can include

  • WhatsApp / chat interface recovery
  • Gateway, plugin, and model access troubleshooting
  • Cron job and scheduled workflow checks
  • Saved skill validation before rescheduling
  • Log review and repair/doctor flow support
  • Clear next-step recommendations after failures

Common issues

  • “My WhatsApp agent stopped responding.”
  • “The system says the model is rate-limited.”
  • “The cron job says it ran, but no report arrived.”
  • “The workflow says it fixed itself, but the real output is missing.”
  • “The saved skill still exists, but I’m not sure whether it is safe to schedule again.”

What this is not

This is not a full security audit, unlimited monitoring, or a guarantee that every downstream system is fixed in one session. The focus is controlled recovery, validation, and the next safe step.

What I do

OpenClaw consulting, implementation, and AI workflow audits

The entry offer is the €99 audit. The larger offer is implementation: turning one valuable workflow into a working operating system with clear approval gates, source rules, and handover.

Need scoping before a full build? See workflow design & scoping. Need specialist roles and routing across several steps? See the advanced multi-agent lane.

01

Operational Audit

I diagnose where follow-up, handoffs, or admin drag are leaking and decide whether the next move should be workflow design, direct implementation, or a more advanced architecture.

See the AI Workflow Audit

02

Workflow Design & Roadmap

You receive a build-ready workflow brief: the first workflow, the approval boundaries, the tool choices, and the cleanest sequence into implementation.

See workflow design & scoping

03

Production Deployment

Full setup on your VPS or server. OpenClaw connected to your CRM, email, Telegram, and workflows. Production-grade security included.

See OpenClaw implementation

04

Handover & Training

1:1 walkthrough of your new system. You own it — no dependency on me. I stay available for 30 days post-launch for refinements.

05

Maintenance & Reliability Support

When operational AI workflows break after launch, OpenClaw can help restore the interface, validate saved workflows, check schedules, review logs, and define the next safe step.

See maintenance support

What this can look like in your business

Practical AI systems, applied to real operations.

Not vague “AI transformation.” Practical systems that remove manual work, speed up decisions, and make revenue-critical operations more reliable. Built around your actual workflows, with clear ownership, measurable outcomes, and implementation that holds up in the real world.

01

Turn inbound leads into qualified opportunities

A multi-agent lead handling system can capture inbound enquiries, enrich the company and contact, score fit, update the CRM, and draft the right follow-up within minutes. Instead of leads sitting in inboxes or getting handled inconsistently, your pipeline moves faster with better context and less admin.

02

Automate delivery operations without losing control

Client onboarding, reporting, handovers, approvals, and recurring delivery tasks can be turned into accountable workflows that route work to the right people and systems automatically. The result is less operational drag, fewer dropped balls, and a delivery engine that scales without adding chaos.

03

Build an internal AI operator for repetitive high-value work

If your team repeats the same research, analysis, QA, documentation, or support tasks every week, those workflows can be broken into specialist agents with clear rules and checkpoints. You keep human oversight where it matters, while the system handles the repeatable work faster, more consistently, and with full traceability.

If you can point to the bottleneck, we can usually design the system around it.

Anonymized proof signals

What this looks like when it works in a real business

These are anonymized examples of the kinds of operational improvements I design for businesses and teams. The point is not flashy AI output. The point is cleaner execution where the business was previously leaking momentum.

Proof pattern 01

Lead handling moved from inbox chaos to structured follow-up

A founder-led lead-handling workflow was redesigned so inbound context could be captured, reviewed, and turned into faster first-pass follow-up instead of sitting in scattered threads.

Outcome direction: less manual triage, cleaner qualification, fewer warm leads cooling down before action.

Proof pattern 02

Post-call execution stopped depending on memory

A delivery workflow was tightened so calls could produce structured summaries, action items, and follow-up drafts instead of loose notes and delayed next steps.

Outcome direction: faster follow-up, clearer ownership, less execution leakage between conversations and delivery.

Proof pattern 03

AI support added capacity without removing accountability

The workflow used AI for drafting, structuring, and routing while keeping commercial judgment and final approvals with the operator.

Outcome direction: more output and continuity without creating a system the business no longer trusts.

Proof approach

Practical AI workflows. Not automation theater.

I design AI-assisted workflows for businesses and teams that need fewer missed follow-ups, less manual admin, and stronger execution without piling on complexity.

What this means in practice

  • Reduce manual drag without building a fragile stack
  • Keep commercial judgment and final accountability human-led
  • Make the right next step easier after calls, meetings, and client interactions

Ideal fit

Who this is for

AI will make your team faster. It will also show you how much more is possible. The question is whether your systems can keep up.

  • Businesses spending 10+ hours/week on repetitive tasks
  • Founders who want AI but don't have in-house ML engineers
  • Companies that need GDPR-compliant AI (Doctolib-grade experience)
  • Teams for whom AI has created more work — and who need the right setup to absorb that scale.

Deployed systems for

Lead follow-up CRM workflows Client operations Reporting loops Human-approved automation

Investment

Choose your path.

Choose the path that matches how ready you are to implement.

€99 / Hour

AI Workflow Audit

  • 1-on-1 workflow diagnosis
  • First-priority recommendation
  • Remote
Book the €99 AI Workflow Audit
Most Popular
Starting at
€1,500 / Project

Scoped Implementation

  • One valuable workflow designed, built, and rolled out
  • Approval gates, source rules, and handover
  • Remote-first; on-site Cyprus only when justified
Request Implementation Scope

Proof signal 01

Engineer-grade implementation

Built around real workflows, system boundaries, and execution quality — not generic AI fluff.

Proof signal 02

Human accountability stays intact

AI supports drafting, routing, and summaries. Commercial judgment and final decisions stay human-led.

Proof signal 03

Designed to reduce chaos

The goal is fewer missed follow-ups, less admin drag, and clearer next actions after every key interaction.

Choose the next step that matches your intent.

If you already know there is a workflow worth implementing, request implementation scope. If you want a paid diagnostic first, book the €99 AI Workflow Audit.

Best fit

  • Businesses and teams with recurring follow-up or handoff problems
  • Founders or operators carrying too much workflow context manually
  • Teams that want practical implementation, not AI theater

Not the right call if

  • You mostly want generic AI brainstorming without an operational bottleneck
  • You want full autonomy with no human review on important actions
  • You are looking for a cheap chatbot setup rather than workflow design

What you leave the first call with

A clearer diagnosis

We identify where workflow drag, follow-up leakage, or operational friction is actually coming from.

A recommended first workflow

You get clarity on which workflow is worth fixing first instead of trying to automate everything at once.

A realistic implementation path

You leave with a practical next-step direction, including what should stay human-led and what can be supported by AI.

Not ready to jump straight into implementation scope? Start with the AI Workflow Audit and diagnose the first workflow worth fixing.

Serious implementation inquiries should start with the Scoped Implementation request. Direct audit calls stay available when you want diagnosis first.