MOST AI ADVICE
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Reactive — question, answer, done
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Meeting-based and sporadic
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No one carries your context
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Pooled resource, junior in disguise
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Left navigating the rest alone
ACCESS
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One named senior, every month
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One session + async, always on
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Context that builds over time
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Senior only. Named. Accountable.
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Someone in your corner
1 × 60-min working session
Per month, calendar-scheduled
Async channel
1 business day response
One named senior
Stays with you. Builds your context
3-month minimum
30-day notice to exit
WHAT ACCESS INCLUDES
WHAT MAKES THIS DIFFERENT
1
A dedicated senior, not a pool
You know exactly who you're working with. They know your business. No handoffs, no re-explaining.
2
Judgment, not just availability
They tell you what they actually think. Not a summary of what you already said, reframed as insight.
3
No hidden hours
One clear monthly price. No scope creep. No invoice surprises. You know what you're getting.
OUR EXPERTS
Rasheed Sheik Meeran
Data Scientist & AI Engineer
Ex Ericsson, Zenseact
Rasheed is a hands-on builder who takes AI projects from data to deployment. He's built generative AI agents, automated data pipelines, and delivered computer vision applications across automotive, healthcare, and telecom. He moves quickly between different types of problems — from machine learning to cloud architecture to business analytics — without getting lost.
What he's good at
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End-to-end AI solutions that deploy to production
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Generative AI and large language models
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Scalable data pipelines and cloud infrastructure
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Translating technical results into business insights
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Python, machine learning, cloud platforms (Azure, AWS)
What he does
Develops ML and generative AI applications. Automates data pipelines and cloud infrastructure. Builds analytics that teams can use. Works across healthcare, automotive, telecom solving different problems.
Felix Ericsson
Data Scientist & Innovation Lead
Ex Syntronic R&D, Mabel AI
Felix builds AI systems that actually work in the real world. He's led teams developing machine learning models for healthcare — from brain tumor detection to real-time speech translation — and has a track record of turning research into products that deliver measurable business impact. He combines sharp analytical thinking with the ability to move from theory to deployment without losing quality.
What he's good at
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End-to-end AI solutions from research to production
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Leading and mentoring technical teams
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Building reliable systems for regulated industries
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Deploying at scale on cloud platforms (GCP, AWS)
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Python, machine learning, data pipelines
What he does
Develops machine learning and generative AI systems that solve business problems. Builds data pipelines and infrastructure that scale. Leads projects from research phase through to production deployment. Works with teams to ensure solutions are robust and measurable.
Anna Lindahl (Ph.D)
Data Scientist
Ex University of Gothenburg, Swedish Union of Tenants
Anna brings a rare combination: deep technical expertise in language AI, but grounded in solving real business problems. She specializes in taking messy, real-world data and turning it into something a machine can learn from — which means understanding both the technical side and why the data matters. Her PhD focused on making sense of how people actually communicate, not just what the words say.
What she's good at
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Understanding what your data actually tells you
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Building and training AI models on language and text
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Figuring out when an AI system is working — and when it's not
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Teaching teams how language AI actually works
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Python, data analysis, machine learning frameworks
What she does
Cleans and prepares data so models can learn from it. Tests whether language AI performs the way you need it to. Builds classification systems that understand meaning. Trains and fine-tunes language models for specific tasks.