What does Prima Partners do?

Prima Partners is the advisory practice of Prasanna Walimbe. It operates in three modes: AI & IT strategy advisory for CXOs, corporate AI enablement and delivery, and angel investment plus mentoring for early-stage founders in fintech, supply chain and applied AI.

Who is Prasanna Walimbe?

Prasanna Walimbe is a deep-tech operator with 20+ years of experience across AI evaluation and safety, AI/ML architecture, and financial research. He is an alumnus of IIT Kharagpur and IIM Calcutta and a Certified Independent Director advising boards on cross-border AI investments, operations and compliance.

Which sectors does Prima Partners focus on?

Fintech and BFSI, supply chain, manufacturing, and applied AI across enterprise use cases. Assurance work is mapped to the EU AI Act, ISO 42001 and the NIST AI Risk Management Framework.

How do I engage Prima Partners?

Email info@prima-partners.com to start a conversation. Engagements run globally on a remote-first basis from Dubai.

What is AI governance consulting and what frameworks do you use?

AI governance consulting maps an organisation's AI systems, decisions and controls to a recognised risk framework — typically the EU AI Act, ISO 42001 and the NIST AI Risk Management Framework — and closes the gaps. Prima Partners runs checklist-based evaluations, model-risk reviews and board-level assurance for financial services, supply chain and applied-AI use cases.

Do you serve boards as an Independent Director?

Yes. Prasanna Walimbe is a Certified Independent Director and advises boards on AI strategy, cross-border investment and operations, and compliance obligations across jurisdictions — with a specialisation in fintech, supply chain and applied AI.

Do you offer corporate AI training and enablement?

Yes. Corporate AI enablement includes executive workshops, leadership AI literacy, hands-on programmes for delivery teams, and practical playbooks — AI realism vs hype, ML deployment, GTM for AI products, and the founder's mindset inside corporates.

Do you mentor or invest in startups?

Prima Partners writes angel and pre-Series A cheques and provides hands-on mentoring. Current positions span defence technology, artisan-led premium design and manufacturing, AI-powered franchisee onboarding for D2C brands, and memory-module hardware and software, alongside fintech, supply chain and applied AI. Support covers technical architecture, GTM, commercial modelling and board readiness.

Which AI model should an enterprise standardise on?

The Stanford 2026 AI Index shows the performance gap between top models has collapsed, so standardising is now a switching-cost and security decision rather than a capability one. Reframe long-running evaluations around integration risk, data-egress controls and exit paths instead of another round of benchmarks.

Should companies slow junior hiring because of AI?

The Index's data on entry-level task exposure argues for redesigning the junior role, not deleting it. Cutting the pipeline solves an immediate headcount problem but removes the bench that becomes your senior engineers and managers by 2028.

Where do AI agents actually belong on the enterprise roadmap?

The Index's agent-benchmark results locate a narrow band of workflows where agentic systems clear the reliability bar today — mostly bounded, tool-using tasks with human review. Broader deployments across open-ended enterprise workflows are a 2027 conversation and should be scoped as such.

Can enterprises trust reported AI productivity gains?

The Index places self-reported productivity uplift directly beside realised-output figures and the two diverge sharply. Boards should measure cycle time, defect rate and unit economics on specific workflows rather than treat satisfaction survey scores as evidence of P&L impact.

Who should sign off on enterprise AI governance?

The Index's transparency scores show foundation-model vendors are disclosing less each year, so control cannot be inherited from the vendor stack. Governance sign-off belongs with an internal owner running a checklist mapped to the EU AI Act, ISO 42001 and the NIST AI Risk Management Framework.

The AI That Can't Write: What Jev Tells Us About Where Enterprise AI Is Heading

2026-09-23 · Enterprise AI · 7 min read

If a model is right 95% of the time but can't tell you when it's in the other 5%, you can't automate around it.

The analysis

On 15 September TypeSafe released Jev, a model that cannot write a word. It takes context and a set of typed questions and returns a choice, a score or a yes/no probability, each with a confidence number. Within a day of reaching Vercel's AI Gateway it was used by nearly 13% of paid teams. Pricing is quoted at $42 per billion input tokens with no output charge, and response times of 70 to 500 milliseconds.

It is more than a classifier in three ways. It is general-purpose — questions and options are defined at call time. It answers all questions in a single pass, so adding questions barely changes latency. And it is trained to be honest about uncertainty: its method rewards accurate probabilities, not just correct answers. Because the options are fixed, it cannot return an invented one.

The scepticism is fair. Engineers note that a constrained, prefilled LLM gets most of the speed, and open replications show a tuned Qwen 9B model reaching 90.1% agreement with reference labels against Jev's 93.2%. The author's read is that the moat is calibration data and method rather than architecture — more than a wrapper, less than a new paradigm.

The larger point is the direction of travel: open System-One models, fast-and-slow interaction architectures, and reliability harnesses that wrap small models in deterministic validators. For enterprises this means routing high-volume, fixed-answer decisions to cheap calibrated models, reserving frontier reasoning for genuinely open problems, and — most importantly — deciding who sets and owns the confidence thresholds before the volume arrives.

Full essay on Substack: The AI That Can't Write: What Jev Tells Us About Where Enterprise AI Is Heading.

More on Enterprise AI

Discuss this with Prasanna: info@prima-partners.com · book a 30-minute call.