A consultancy model designed for a world with more information, faster tools, and the same need for accountable judgment.
Technology should widen the view—not obscure responsibility.
Research got faster. Decisions did not get easier.
Apexion pairs specialized AI-assisted research workflows with human judgment. The technology helps collect, compare, and structure evidence; the advisor challenges what it means.
Engagements begin with a specific business question and end with a reviewable recommendation—not an autonomous decision, a generic report, or a borrowed sense of certainty.
The standard behind the work.
The method may evolve. These commitments do not.
- 01
Show the machinery
Disclose where AI supports the work and where human judgment changes or limits the output.
- 02
Name the unknowns
State assumptions, gaps, and confidence levels with the same clarity as the recommendation.
- 03
Keep ownership human
A person remains accountable for what is presented; the client retains every final decision.
- 04
Respect the context
Use client information only for the agreed purpose and protect sensitive material by design.
A name on every recommendation.
Each engagement has one advisor accountable for what is presented, and a discipline they are expected to defend.
Annika Lindqvist
Founder & Principal Advisor
Owns the recommendation on every engagement and signs off on what is presented.
Sofie Dahlgaard
Partner, Growth & Go-to-Market
Market selection, positioning, and the pipeline experiments that follow from them.
Elise Nordström
Head of Research
Turns scattered public and client evidence into a decision narrative that can be challenged.
Margareta Holm
Senior Advisor, Finance & Risk
Operating models, scenarios, and the controls that keep a plan honest.
Jonas Berg
Advisor, Operations & Supply Chain
Where cost, lead time, and vendor concentration actually come from.
Erik Sandvik
Analyst, Technology & Architecture
Build-versus-buy, platform risk, and what a system will cost to keep running.