Enterprise AI agents
Your enterprise, run by agents. People review what matters.
I turn your enterprise architecture into multi-agent workflows. Each agent acts inside written permissions, and a named person signs off the decisions that matter.
- Multi-agent workflows
- Human review where it matters
- Proven on your data
- Audit trail
The challenge
Your AI pilot worked. It never reached production.
Gartner predicts over 40% of agentic AI projects will be cancelled by the end of 2027 because of rising costs, unclear business value or weak risk controls. The model is rarely the problem. What is missing is a defined result, a way to prove it and someone accountable for it.
What I own
Map, design, prove, run. Agents act. People review.
01
Map
Your enterprise architecture: the systems, data and processes, and where agents pay back. Including saying no where simpler automation is enough.
02
Design
Multi-agent workflows: which agent does what, what it may read, write and decide, and when it asks a person to review.
03
Prove
Value review and evals on your own data before anything goes live.
04
Run
Production with permissions, audit trail, cost controls and a named reviewer for every decision that needs one. Then your team runs it, with the decisions in writing.
Agents do the work. Accountability stays with people. I design where that line sits.
Who you work with
Fractional CTO and product lead, Vienna
I have led enterprise platform development, founded an enterprise SaaS company, and today run agents in production and in my own products. I own the process decision, the architecture and the result together.
Delivered within my work as Fractional CTO, Product Lead or AI Architect.
“Kristian is certainly one of the top picks in his field.”
Agents do the work. One accountable lead answers for the result.
- 25 years
- In software architecture and product, in Europe and North America.
- 50+
- Product launches across startups and enterprises.
- 5.0★★★★★
- Upwork rating, Top Rated Plus, more than $500K earned.
How it works
From pilot to production. Proven on your data first.
The architecture is mapped first, the first workflow is proven on your data next, and the agents take the full volume last.
- 1
Process review
Your systems, data and processes mapped, and the workflows assessed on value, risk and the state of the data. The first workflow is picked, or none, if simpler automation does the job.
- 2
Value review and evals
The result defined with the process owner, and evals run on your own data before anything goes live.
- 3
Pilot in production
The agents run the workflow on a share of real cases, acting on their own and asking a named reviewer where a wrong decision has consequences.
- 4
Scale
Permissions, audit trail and cost per result in place, then the agents take the full volume.
- 5
Handover or ongoing
Your team runs it with documentation and every decision in writing, or I stay on for the next workflow.
Plans
A fixed price for each step. Start with the process review.
Each plan builds on the one before it, at a fixed price agreed before the work starts. Most start with the process review and decide the next step once the numbers are on the table.
Process review
$4,900
3 weeks
Two to three candidate processes assessed on value, risk and data. One picked, with the expected result and measurement plan.
Book a callProven on data
Recommended$14,900
6 weeks
The process review, then the result defined with the process owner and the agent evaluated on your own data.
Book a callPilot in production
$29,900
10 weeks
Proven on your data, then the agent running a share of real cases with permissions, audit trail, cost per result and a named owner.
Book a callScale and next processes
Let's talk
Milestones
The agent on the full volume, and the next processes on the same frame of permissions, evals and cost controls.
Talk it through- Your systems and data
- Written decisions
- Audit trail
- A named owner for every decision
How it starts
Bring these to the first call.
Your answers shape the process review.
- 1
Which business process takes the most manual work today?
- 2
Which AI pilots have you run, and where did they stop?
- 3
What result would make the process worth handing to an agent?
- 4
Which systems and data does the process touch?
- 5
Who signs off today, and who would own the agent's decisions?
Roles and outcomes
Delivered by one person. The roles behind the process.
An agent in production is delivered within my fractional CTO or AI architect work. Take the role that fits, or one of the other outcomes.
SaaS & AI product launch
Agentic frame included
A SaaS or AI MVP launched for paying customers, at a fixed price, in weeks.
Enterprise AI agents
This page · Every decision has an owner
Multi-agent workflows across your business, with human review where it matters.
AI agent evaluation
Right problem, solved right
AI agents that solve the right problem, proven with evals end to end.
Fractional CTO
Technical direction you can trust
Technical direction, architecture calls and your development team, owned part-time.
Product Lead
What to build, and why
What gets built and in which order, turned into specs your team can ship.
AI Architect
AI that holds in production
AI features and agents that hold in production, with evals and permissions.
Industries
See it in your industry. The first process depends on your field.
Each page shows where agents fit first in that industry.
- Software and SaaS companies
- Digital and marketing agencies
- Healthcare and HealthTech
- FinTech, financial services and M&A
- Real estate and PropTech
- Education and EdTech
- B2B e-commerce and wholesale
- Media and digital content
- Insurance and InsurTech
- Life sciences and regulated software
- Restaurants and hospitality
- Mobility, travel and aviation
- Government and public sector
Questions
FAQ
How do multiple agents work together?
As one workflow across your architecture. Each agent has its own task and permissions, hands its result to the next one, and acts on its own until a decision needs a person. Then it asks a named reviewer and waits. Every handoff and decision is logged with its reason.
Why prove one workflow first?
Because a result has to be proven before it scales. The first workflow gives one measurable result, named reviewers and one audit trail. The next workflows reuse the same frame of permissions, evals and cost controls, so they go faster.
What if simpler automation is enough?
Then that is the recommendation. Rules and workflow automation are cheaper and more predictable. An agent earns its place where the process needs judgement on unstructured input.
How do you keep agents inside their permissions?
Each agent gets an explicit list of what it may read, write and decide. Anything outside that list goes to a named person for review, and every action and decision is logged with the reason behind it.
What does an agent cost to run?
Cost per result is measured during the pilot on your own volume, before the agent takes the full process. Cost controls cap model spend, and the business case is written against that number.
How is it priced?
At a fixed price per plan: the process review $4,900, proven on your data $14,900 and a pilot in production $29,900, excluding VAT. Scaling and the next processes are scoped with you.
Do you work with our IT, security and existing vendors?
Yes. The agent runs in your systems and accounts, under your security and compliance requirements. Your IT, security and process owners are part of the decisions, and every decision is written down.
Get in touch
Start with a call.
We go through the processes that take the most manual work and the pilots you have run. You leave with a view on which process is worth taking to production.
Services: SaaS & AI product launchEnterprise AI agentsAI agent evaluationFractional CTOProduct LeadAI Architect