Your team is brilliant. And buried.
~40% of expert time is structured routine. Agents now handle 60%+ of it — your team is freed for the work only they can do.
The invisible capacity drain.
- 40%
- of expert time goes into structured routine
- 3×
- more time compiling than deciding
"We have 30 people doing the work of 70. We can't hire. Could agents go in the org chart?"
Today in the enterprise.
Tomorrow with agents.
Quarterly report for the board
1 person, 1 week, every quarter.
New hire onboarding
Weeks until productive.
Competitive analysis
Outdated the day it's finished.
Follow-ups
Fall through — nobody has time.
Project handover
Knowledge leaves with the person.
Agent drafts from live data
4 hours instead of 5 days.
Agent knows every process
Productive from day 1.
Agent scans daily
Always current, automatic.
Agent tracks proactively
No contact falls through.
Agent is the memory
Knowledge stays, people change.
This isn't a pitch.
This is our daily reality.
A hybrid team — experts alongside AI agents. In production since January 2026.
- 58k+
- documents in the Knowledge Graph
- 20
- autonomous processes (crons) 24/7
- 60%+
- of our structured routine handled by agents, measured per task
Per-task economics
Senior expert
€150–200
1–2 hours of skilled time
One proposal draft
~120× cheaper
Agent
€1.27
~30 seconds of compute
We track every agent to the cent.
Fleet cost tracker, daily digests, per-task costs to two decimals. Most AI transformation stories can't say what their agents cost. We can.
Meet the new MING hires
6 live · 1 onboarding · 1 hiring
Chief of Staff
Owns
Founder ops
Pipeline, clients, inbox, 24/7.
Employee #001
MING started with Lola. Before the playbook, before the rest of the roster — she was the first hire we trusted with founder-level work. She's still the agent we ask first when something new lands on the desk.
Engineering
Owns
Shipping pipeline
Code, deploys, infra.
Multi-venture Strategy
Owns
Portfolio synthesis
Cross-org context, weekly synthesis.
Data & Pipeline
Owns
Pipeline Intelligence
Built Pipeline Intelligence. Enriches deals, scores health, flags risk.
Hyperize Agent
Owns
Hyperize GEO ops
GEO CLI operations — prompt regression, provider coverage.
Client Intelligence
Owns
Account intel
Account research, briefings, signal scans.
Finance & Ops
Owns
Finance ops
Cash, runway, invoicing — learning the ropes.
- 6
- agents live
- 7,184
- tasks last month
- 100%
- under named human ownership
Want an agent like Lola in your org? Start with a briefing — we read it, then design the role.
Start with a briefing
What our agents
did yesterday.
Most companies don't have an AI problem. They have an organisation problem. A better tool makes an overloaded employee overloaded faster. The real question: which work is done by an agent, and which stays with humans?
The variable that triples success isn't the model. It's who builds it with you.
- 67%
- pilot success rate when internal specialists build with external expertise
- 22%
- success rate when IT builds it alone
- 3×
- the partnership multiplier, independent of technology, sector, or model
Source: MIT Project NANDA, "State of AI in Business 2025"
The bottleneck is organisational, not technical. That is the layer we design.
Sales Enablement Agents
Marketing Agents
Service Agents
Operations Agents
How the organisation works.
How we recruit agents.
We assemble agents the way you'd hire a team member. A role with responsibilities. Skills they need. Playbooks they follow. Governance they operate within. Not a config file. A colleague your team can actually work with.
How agents and humans align.
The interface between humans and agents. Most agent platforms solve human-in-the-loop by interrupting humans for approvals. We solve it the way organisations actually decide things. In the meeting. Humans talk, debate, align. We capture what was agreed, what wasn't, who owns what next, and where every claim came from. Decisions route to whoever executes them. Humans, agents, both. No approval queues. No supervision theatre. Execution starts on real consensus.
We don't reinvent the plumbing, we design the organisation that uses it.
The method,
in brief.
Three frameworks run every engagement. The depth lives in Insights; here is what each one does.
Not everyone can do this. The technology is available. The challenge is building agents that actually work in the enterprise. 15 years of enterprise experience with 50+ clients: Bosch, Siemens, MANN+HUMMEL, Voith, Henkel. We know the systems, the politics, the processes.
Four levels of autonomy.
One principle: earn trust.
Not all agents operate at the same level of independence. The right level depends on the task, the stakes, and how much trust has been built.
Suggests
Level 1Agent produces output. Human reviews and approves before anything happens. Always safe.
Drafts
Level 2Agent drafts actions — emails, documents, updates — for human review before sending. One click to approve or edit.
Acts with log
Level 3Agent acts autonomously on defined, lower-risk tasks. Every action is logged and reviewable. Humans can intervene.
Fully autonomous
Level 4Agent acts and reports. Used only for well-defined, reversible tasks where trust is fully established.
Start at Level 1. Promote agents as trust is earned. Exactly like a new hire.
The questions every
champion gets asked.
If you're the one carrying this internally, these are the answers.
What does it actually cost?
Engagements start at €9,500 for a half-day workshop that produces a capacity model and your first agent specification. A first production agent is €20–25K. And you see the per-task economics from day one: we track every agent to the cent.
Will this replace my people?
No. Judgment, relationships, and accountability stay human. Agents take the structured routine that buries your experts. It is a job redesign, not a job elimination: headcount preserved, senior people doing senior work again.
Won't this expose our data?
Agents hold no production credentials. Data access is tiered per role and per task, every action is logged and reviewable, and no agent goes to production without IT governance sign-off.
Who needs to be at the table?
Three sides. IT owns governance: architecture, data access, security. Business owns the what and the why: role redesign and ROI. We bring the use cases, the agent design, and the build, inside your governance framework.
What if our data is fragmented?
“We need a data project first” is usually a delay tactic. The right first agent runs on data that already exists, hidden in emails, documents, tickets, or one person's head.
Start small.
Scale what works.
Workshop
Workshop + First Agent
RecommendedHybrid Org Programme
All prices excl. VAT. Travel costs outside DACH billed separately.
Voices
" MING helped us deeply understand the needs of our users and quickly build an AI PoC to validate the value of our ideas — without losing time and money. Working with MING is fast, efficient and engaging: a great team that really understands AI and UX. "
Half a day.
Three roles.
One Concept Paper.
In the same agent-formation environment we run our own agents on.
We come to you. Three roles from your division. Where is the structural pressure highest? You leave with a configured environment: first use case, ROI model, plan.
Matthias or Sebastian respond personally. No sales team. No BDR.
Agent formation environment — built and run by MING Labs.
Onboarding
½ day on-site, three roles
Formation environment configured
Within 1 week
First agent in production
2–4 weeks
Not a methodology. The tooling we built for ourselves — and run on ourselves.
Your team is brilliant. Now give them room.
