Inception Fund

Still in pre-training. Backing New Nordic made technical brilliance at the earliest inception stages.

www.inceptionfund.vc

In pre-training...

Zenith Ventures

Founder and operator turned VC. Backing obsessed Nordic B2B software and vertical AI founders from the earliest stages. 

No-nonsense, hands-on and fighting for founders.

General Partner

Stealth AI Startup

Pre-seed Investor

Natively

Build and launch native mobile apps with AI.

www.natively.dev

Lovable

Building the last piece of software.

Careers: https://lovable.dev/careers

www.lovable.dev

Angel Investor

Vantel (YC W25)

AI Software for commercial insurance brokers (YC W25).

www.vantel.com

Pre-seed Investor 

Tandem Health

Helping clinicians focus on providing care instead of on administrative tasks through AI and automation.

Careers: https://jobs.ashbyhq.com/tandem-health 

www.tandemhealth.ai

Tzafon

An applied AI research & development firm looking to push the boundaries of what machines are capable of through the intersection of AI & software engineering.

www.tzafon.ai

Lightbringer

Navigate and protect your IP and patent journey with AI.

Careers: https://www.lightbringer.com/apply

www.lightbringer.com

Seed Investor

Pruna AI

The AI optimization engine for ML teams seeking to simplify scalable inference.

Careers: https://careers.pruna.ai/

www.pruna.ai

Data & AI/ML Entrepreneur | Early Stage Investor

Over a decade of experience within Big Tech, B2B software, Data and AI Infrastructure as a founder, operator and investor.

Passionate about bringing new and paradigm-shifting technologies to market. This passion has led me to a over decade-long entrepreneurial career focused on emerging software industries and global markets - from ML & Data Infrastructure startups and venture capital funds to Fortune 500 technology leaders such as Google. 

Raised +$50M in early-stage funding from top VCs as a founder and operator. 

A big believer in people, data, design and telling a story. Passionate about building new products with the right GTM, messaging and growing teams that do so.

Deep understanding of the venture capital, private equity, SaaS, cloud, data and AI ecosystems with solid global relationships at all levels.

Frequent keynote speaker on topics around data, AI, startups and venture capital. Considered as one of the top AI & data thought leaders in the Nordics.

Oliver Molander

I don't think people truly understand how early we're in enterprise adoption of AI agents.

McKinsey just released their 2025 AI report. 

Some nuggets:

1️⃣ 90% of companies “use AI,” but 67% are still stuck in pilot mode. Corporate AI theater is alive and well.

2️⃣ 62% of orgs are experimenting with AI agents, 23% are scaling AI agents. Most are in tech and healthcare.

3️⃣ The impact gap is massive. 64% say AI helps innovation, but only 39% see real EBIT gains. 

4️⃣ The high performers (top 6%) think bigger. They rebuild workflows, set growth goals, and invest real budgets not just PoCs.

5️⃣ Leaders who own AI personally are 3x more likely to scale it. Makes sense.

6️⃣ The winners use AI to transform how work gets done, not just speed it up.

7️⃣ The average company measures efficiency. The best ones measure how fast their agents can act.

8️⃣ Risk management is catching up with 51% have already seen AI backfire, mostly from inaccuracy.

9️⃣ The workforce impact is foggy. 32% expect cuts, 13% expect growth, everyone else is guessing.

Agentic AI looks magical in demos, but scaling it across teams and systems (especially in enterprise settings) is where it still breaks. You can do basic single-step automation reliably right now (tool calling).

As Andrej Karpathy recently noted on LLM agents:

"My critique of the industry is more in overshooting the tooling w.r.t. present capability."

Bottom line: we're still super early, this transformation will go on for another decade.

I'm bullish, but this will take a bit longer than we think, having fully autonomous agents. Just like autonomous driving took a bit longer than we thought, but here we are.

E.g. one of the biggest challenges in building AI agents today is agents' long-term memory.

#artificialintelligence

CS graduate (M.S., AI, GPA 4.0) and former AWS SDE Intern with proven experience delivering scalable AI and MLOps solutions.

At Amazon, built a log dashboard and automated CDK/CI-CD deployments — cut rollout time by 90% and reduced analysis time by up to 60%.

At Mississippi State University, advanced research with Stanford/Princeton using GANs & Diffusion Models — improved image restoration by 20%.

In healthcare AI, boosted model accuracy and reduced inference latency with serverless AWS pipelines.

Core strengths: AI/ML (LLMs, CV, RAG, GenAI), MLOps (Docker, Kubernetes, CI/CD), and Cloud (AWS, GCP).

Currently seeking full-time Software Engineering, AI/ML, or MLOps roles where I can drive measurable impact at scale.

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Oliver Molander

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The Battle

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Sushant Gautam

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Oliver Molander's LinkedIn Performance

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