N※N

Meet Jatin Sandilya: The Founder Driving Reliable Integrations With AI

  //humor-quirks.news-articles.net/content/2025/08 .. under-driving-reliable-integrations-with-ai.html
  Published in Humor and Quirks on Friday, August 29th 2025 at 13:17 GMT by USA Today
          ^{🞛 This publication is a summary or evaluation of another publication 🞛 This publication contains editorial commentary or bias from the source}

Meet Jatin Sandilya: The Architect of AI‑First, Reliability‑First Integration Platforms

When Jatin Sandilya first stepped into the AI conversation, the tech world was still grappling with questions of “what does it mean to trust an algorithm?” Today, a growing number of enterprise software teams are confronted by a far more practical dilemma: how can they embed sophisticated AI models into mission‑critical workflows without compromising reliability, security, or compliance? Sandilya’s answer is a purpose‑built platform that turns AI’s promise into a dependable operational asset. In a recent contributor article on USA Today—complete with interviews, screenshots, and a few linked press releases—the author unpacks Sandilya’s journey from a systems engineer to the founder of a company that is redefining the intersection of artificial intelligence and enterprise reliability.

From System Reliability to AI Integration

Sandilya’s roots are firmly planted in the world of system reliability. A graduate of Stanford University with a degree in Computer Science, he began his career at Amazon Web Services, where he led a team that engineered the first “fail‑over” mechanisms for the company's global data‑center fleet. “You learn early that if a single node fails, the entire system can be at risk,” he recalls in the interview. “I didn’t want that same risk to be magnified when we began pulling in third‑party AI services.”

After a stint at Microsoft’s Azure AI Lab—where he helped design the AI governance framework that would later be incorporated into Azure’s compliance suite—Sandilya realized a growing gap: most AI solutions are “black boxes” that can be deployed but not reliably orchestrated in production. This insight spurred the launch of Reliably.ai (formerly known as CortexConnect), a SaaS platform that blends the orchestration logic of traditional Enterprise Service Bus (ESB) tools with real‑time AI monitoring and risk mitigation.

The Reliability‑First Philosophy

Sandilya’s platform is built around three core pillars, each addressing a common pain point that enterprises face when integrating generative AI:

In a side‑by‑side demo included in the article, Sandilya showcases how the platform can integrate a GPT‑4 model into a finance firm’s risk‑analysis pipeline while ensuring that the model’s predictions remain within a statistically defined “confidence band.” If the band is breached, the system automatically routes the request to a simpler rule‑based engine and logs the incident for future review—effectively turning a risky AI call into a controllable, auditable event.

Building a Trustworthy Ecosystem

The article highlights that sandilya’s vision goes beyond technology. He is actively involved in shaping industry standards around AI reliability. The piece quotes him saying, “We can’t just build great products; we have to build the ecosystem that allows everyone to use them safely.” As a result, he’s joined the newly formed AI Reliability Consortium (AI‑RC), a coalition of leading AI vendors and compliance bodies that aims to codify best practices for AI deployment.

Sandilya’s commitment to transparency is further underscored by an open‑source initiative. The platform’s core orchestration engine is now available on GitHub under an Apache 2.0 license, accompanied by extensive documentation and sample use‑cases. The article points readers to the repository for developers who want to experiment with the platform before committing to a paid tier.

Funding, Partnerships, and Future Roadmap

Sandilya’s startup has already secured a $12 million Series A round from a consortium of venture funds that specialize in AI infrastructure, including GV (formerly Google Ventures) and CapitalG. The funding is earmarked for expanding the platform’s data‑privacy modules and forging strategic partnerships with cloud providers.

In the article, the author interviewed Sandilya’s CFO, who disclosed that Reliably.ai is planning to launch a “Compliance‑as‑a‑Service” (CaaS) layer by Q3 2026. This layer will automatically align deployed models with regional data‑localization laws, a feature that will be particularly attractive to multinational firms operating across the EU, US, and Asia.

Key Takeaways for Enterprise Tech Leaders

1. AI is Not Inherently Unreliable—It’s How You Deploy It
   The article stresses that reliability problems stem from poor integration rather than from AI models themselves. Platforms that weave governance, monitoring, and dynamic routing into the deployment process can mitigate most of these risks.

2. Audit Trails Are a Must‑Have, Not a Nice‑To‑Have
   Sandilya’s product makes logging and auditing effortless. For firms in regulated sectors—healthcare, finance, public safety—this can be the difference between meeting compliance and facing costly fines.

3. Vendor Lock‑In Is a Barrier to Adoption
   By providing a generic orchestration layer, Reliably.ai allows enterprises to mix and match models from multiple vendors (OpenAI, Anthropic, Cohere, etc.) without rewriting their codebases.

4. Open‑Source Bridges the Gap Between Innovation and Safety
   The public GitHub repository demonstrates that open‑source tools can coexist with proprietary offerings, fostering a broader ecosystem that benefits both developers and businesses.

Closing Thoughts

The USA Today piece presents Jatin Sandilya as a seasoned reliability engineer who has translated his domain expertise into a forward‑thinking solution for one of the most pressing challenges of modern AI adoption. Whether you’re a product manager looking to embed an LLM into a customer‑facing chatbot, or a CTO tasked with ensuring that an AI‑driven predictive model remains compliant, Sandilya’s platform offers a compelling blueprint for turning AI’s theoretical promise into a proven, reliable operational asset.

For those who want to dig deeper, the article links to several additional resources: Sandilya’s personal blog post on “Why Reliability Matters in AI,” a press release announcing the Series A funding, and the official product landing page where one can sign up for a free trial. If you’re intrigued by the idea of turning AI from a risk into an advantage, Jatin Sandilya’s work is a conversation you can’t afford to miss.