Valistry

Helping enterprises maximize the value of every AI investment.

Valistry shows companies what AI costs, who owns it, what value it creates, and whether it is used safely. Then they can adopt and scale AI with confidence.

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Building economic confidence into enterprise AI.

Our vision

Every company realizes the full value of its AI investments.

A future where companies maximize the value of every AI dollar and keep track of cost, ownership and business outcomes as use grows.

Our mission

Enable enterprises to adopt and scale AI with confidence.

Valistry helps enterprises discover their AI estate, attribute spend to owners and outcomes, optimize the changes worth making, and govern the tools in use, so waste, blind spots and unaccountable usage go down.

Gaurav Arora

Gaurav Arora

Founder, Valistry

  • Eleven years at AWS, building and leading its startup business across Asia Pacific and Japan and scaling it to more than $1 billion in annual revenue.
  • Led global partnerships, startups and product-led growth at DevRev, working closely with enterprises adopting generative and agentic AI.
  • Earlier, venture capital at Prime Ventures and engineering at AMD and Texas Instruments.
  • IIT Delhi graduate and Cambridge MBA.

From cloud adoption to AI economics.

During my eleven years at AWS, I saw the cloud adoption curve unfold from its early days of digital transformation to the disciplines of cost optimization, governance and security that followed. As cloud adoption grew, so did an important customer question: are we getting the right value from what we are spending?

Helping customers reduce and optimize their cloud costs was part of how success was measured at AWS. That focus built trust, and gave customers greater confidence to expand.

Years later at DevRev, while working with enterprises considering agentic AI, a similar concern began to surface. Leaders were excited about what AI could do, but cautious about making it broadly available without a clear view of the resulting cost and value.

They did not want to encourage adoption one week and restrict it the next because spending had grown faster than their ability to understand it.

The challenge with AI is that its economics are distributed. Spend can sit across models, agents, APIs, cloud infrastructure, coding assistants and employee applications — often before an owner, a purpose or a measurable outcome has been established.

As AI becomes more embedded across the enterprise, economic confidence will become one of its most important enablers. Companies will need to know what they are spending, where it is going, who owns it and whether it is creating meaningful business value. Valistry grew from that belief.

Maximizing value from AI will not be a one-time optimization exercise. It will be an ongoing discipline — built through visibility, accountability, better decisions and continuous governance.

That is the idea behind Valistry: the discipline of maximizing value.

Four principles behind every Valistry number.

  1. Value before cost

    The cheapest model is not automatically the best business decision. Optimization protects the outcome; it does not only reduce usage.

  2. Evidence before claims

    An opportunity is expected value. It becomes realized value after the change is implemented and measured.

  3. Clarity over false precision

    Spend with no owner yet, or an outcome not measured yet, shows as a gap. Valistry never estimates it.

  4. Governance enables adoption

    Approved tools, clear owners and budgets let teams adopt AI with more confidence and the same freedom.

Adopt AI with a clearer view of its value.

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