Hacking the Immigration Code: An Interview with OpenSphere CEO Atal Agarwal

America’s immigration system stands at a crossroads, burdened by complexity, lengthy processing times, and barriers that often exclude the very talent the nation seeks to attract. While traditional immigration applications can take months to navigate through intricate legal requirements, the system desperately needs innovation to match the speed and scale of today’s global talent marketplace. Enter Atal Agarwal, a visionary technologist who has turned his own immigration journey into a mission to democratize access to the American dream through artificial intelligence.

1) Please tell us more about yourself.

I’m Atal Agarwal, founder and CEO of OpenSphere, where we’re leveraging AI to democratize U.S. immigration access for extraordinary talent worldwide. My journey to this mission has been deeply personal. As an immigrant who navigated the system’s complexities firsthand, I’ve experienced both America’s tremendous opportunities and its frustrating barriers.

I graduated with a dual degree in Mining Engineering from IIT Kharagpur, where I served as student president after winning one of the largest electoral victories in the institute’s history. I later earned my Master’s in Technology Management from UC Santa Barbara, where I co-founded MoreSolar, a cleantech startup that won the New Venture Competition and secured angel investment.

Over the past five years, I’ve led product development at healthcare technology companies like eHealth and Castlight Health; building platforms serving millions of users. At eHealth, I developed products that helped over 3 million people access COVID-19 testing, demonstrating how thoughtful technology can solve real-world problems at scale.

What drives me is the belief that America’s greatest strength lies in attracting global talent, but our immigration system often fails to efficiently process extraordinary individuals who could contribute immensely to innovation and economic growth. OpenSphere represents my commitment to fixing this broken system through technology, making the pathway to American opportunity more accessible and transparent.

2) The O-1 visa is often called the “genius visa,” yet many qualified professionals don’t realize they meet the criteria for extraordinary ability. How does OpenSphere’s AI platform help identify and evaluate potential candidates across different immigration pathways like O-1A, EB-1A, and EB-2 NIW?

The “extraordinary ability” standard is one of the most misunderstood aspects of U.S. immigration law. Many brilliant professionals assume they’re not qualified because they interpret “extraordinary” to mean Nobel Prize winners or Olympic athletes. In reality, multiple pathways exist for high-skilled professionals: O-1A for temporary status, EB-1A for permanent residency, and EB-2 National Interest Waiver for those whose work benefits the United States.

Our AI platform addresses this knowledge gap through sophisticated pattern recognition that analyzes an individual’s background against thousands of successful cases across all three categories. We’ve discovered that extraordinary ability manifests differently across fields and visa types. A software engineer’s path to demonstrating extraordinary ability for an O-1A looks different from building an EB-1A case, while an EB-2 NIW emphasizes national interest rather than just individual achievement.

Our assessment algorithm evaluates the eight key areas for O-1A and EB-1A cases: awards, memberships in prestigious organizations, published material, judging others’ work, original contributions, scholarly publications, critical roles at distinguished organizations, and high compensation. For EB-2 NIW cases, we focus on demonstrating substantial merit, national importance, and whether waiving labor certification serves U.S. interests.

What’s innovative is how our AI identifies optimal pathways. We might recommend that a startup founder pursue O-1A initially while building toward EB-1A, or suggest that a researcher’s work pattern aligns better with EB-2 NIW given their focus on societal impact.

3) OpenSphere serves as a comprehensive immigration marketplace connecting applicants with attorneys and providing AI-driven insights. What specific technological innovations power this platform, and how do they improve success rates?

Our platform is built on interconnected AI systems that optimize every aspect of the immigration application process. The core innovation is our pattern recognition engine, which has analyzed thousands of successful petitions to identify specific combinations of evidence, presentation strategies, and supporting documentation that correlate with approval rates across different fields and USCIS service centers.

This analysis revealed insights that traditional legal practice often misses. We discovered that certain types of industry recognition carry significantly more weight than others, that evidence sequence and framing matters tremendously, and that different USCIS adjudicators show measurable preferences for specific presentation styles. Our AI captures these nuanced patterns and applies them to individual cases.

Our document intelligence system uses natural language processing to evaluate supporting material strength and relevance. When applicants upload recommendation letters, our AI analyzes content, language patterns, and alignment with visa criteria, then provides specific feedback on strengthening weak areas.

The marketplace component leverages these insights to make optimal attorney-client matches, considering track records in specific fields, success rates with similar cases, and expertise with particular evidence types. This matching algorithm significantly improves outcomes by ensuring applicants work with legal professionals who understand their circumstances.

Our continuous learning system means the platform gets smarter with every case, creating a virtuous cycle where success rates improve over time, benefiting the entire applicant community.

4) Your background spans healthcare technology at major companies like eHealth and Castlight Health, where you built products serving millions of users. How do these experiences inform your approach to solving immigration challenges?

My healthcare technology experience has been instrumental because both healthcare and immigration share fundamental challenges: complex regulatory environments, high-stakes decision-making, and systems that often fail the people they’re meant to serve.

At eHealth, I developed COVID-19 testing products that helped over 3 million Americans access care during a critical period. This taught me how to build technology that performs under pressure, with life-changing consequences for users. Immigration decisions carry similar weight – determining whether brilliant individuals can pursue their dreams and contribute their talents to America.

Healthcare technology also taught me about navigating complex, fragmented systems where multiple stakeholders have different incentives. At Castlight Health, we integrated with hundreds of healthcare providers, insurance companies, and benefit administrators. Immigration law presents similar complexity, with USCIS service centers, consulates, attorneys, and applicants all operating within intricate regulatory ecosystems.

Perhaps most importantly, healthcare technology emphasized data-driven personalization. We learned that generic guidance often fails because individual circumstances vary tremendously. Similarly, immigration strategies must be highly personalized based on an applicant’s field, achievement profile, and specific circumstances.

The healthcare experience reinforced the importance of transparency and education – people make better decisions when they understand their options and the reasoning behind recommendations. We’ve applied this principle by making our AI’s reasoning transparent and educating applicants about the immigration process.

5) As AI becomes increasingly integrated into critical decision-making processes, there’s growing discussion around AI policy and governance. How do you navigate the regulatory landscape when applying AI to immigration law, and what role should policy play in governing AI-powered legal services?

The intersection of AI and immigration law sits at the heart of two critical policy debates which are AI governance and immigration reform. This creates a unique regulatory environment that requires careful navigation and proactive engagement with policymakers.

Currently, there’s no specific regulatory framework governing AI applications in immigration services, which creates both opportunities and responsibilities. We’ve taken a conservative, compliance-first approach by ensuring every algorithm recommendation undergoes legal review, and we maintain strict boundaries around what constitutes legal advice versus technological assistance.

The broader AI policy landscape is evolving rapidly. The Biden administration’s AI Executive Order and various state-level initiatives are establishing principles around AI transparency, accountability, and bias prevention that will likely extend to legal services. We’re actively participating in these policy discussions because AI-powered immigration services should be held to the highest standards.

One critical area where policy guidance is needed is data privacy and security. Immigration applications contain highly sensitive personal information, and AI systems require robust data protection frameworks. We’ve implemented enterprise-grade security measures, but industry-wide standards would benefit both service providers and applicants.

Looking forward, I believe smart AI policy should focus on outcomes rather than restricting technology. The goal should be ensuring AI improves access to justice, reduces bias in decision-making, and maintains high standards of professional service.

6) OpenSphere has gained recognition for its high success rates and partnerships with top immigration attorneys. What key metrics and achievements demonstrate the platform’s impact, and how do you ensure quality while scaling?

Our success metrics reflect both efficiency gains and real-world impact on applicants’ lives. We’ve maintained approval rates that consistently exceed industry averages, with our AI-assisted applications showing success rates above 90% across different fields and applicant profiles. More importantly, we’ve reduced average case preparation time significantly while improving the quality and consistency of petition preparation.

One metric I’m particularly proud of is our attorney satisfaction scores. The immigration lawyers in our network report higher efficiency, better client outcomes, and reduced administrative burden when using our platform. This has led to organic growth in our attorney network, with top-tier immigration firms actively seeking partnerships because they see the competitive advantage our tools provide.

Quality assurance while scaling presents unique challenges because mistakes can have severe consequences for applicants’ futures. We’ve addressed this through multiple layers of verification and continuous learning. Every AI recommendation is validated against current immigration law, with our system updated in real-time as regulations change.

Our attorney partnership model is crucial for maintaining quality at scale. Rather than trying to replace legal expertise, we enhance it by providing attorneys with better tools, deeper insights, and more efficient workflows. This creates a quality control mechanism where experienced immigration professionals review AI-generated recommendations and provide feedback that improves our system over time.

7) The intersection of AI and immigration law raises important questions about accuracy, compliance, and the human element in life-changing decisions. How do you balance technological innovation with the need for human oversight and regulatory compliance?

This is perhaps the most critical challenge we face, and we’ve taken a deliberately conservative approach because the stakes are so high. Immigration decisions fundamentally alter people’s lives, families, and careers and there’s no room for error or oversimplification. Our AI is designed to enhance and augment human expertise, not replace the judgment and experience that skilled immigration attorneys bring to complex cases.

Our compliance framework operates on multiple levels. Our AI systems are trained exclusively on successful cases and current legal standards, with continuous updates as immigration policies evolve. We maintain direct relationships with leading immigration law firms who provide ongoing guidance on regulatory changes and best practices.

The human oversight element is built into our platform architecture. While our AI can efficiently analyze evidence and generate initial petition drafts, final strategic decisions always involve human review. Our attorney partners use our tools to accelerate their work and improve consistency, but they retain full responsibility for case strategy and legal interpretation.

We’ve implemented extensive transparency measures so both attorneys and applicants understand how our AI reaches its recommendations. Rather than providing black-box suggestions, our platform explains the reasoning behind each recommendation, cites relevant legal precedents, and highlights areas where human judgment is particularly important. This transparency enables attorneys to evaluate our suggestions critically and make informed decisions about implementation.

8) Looking at the broader immigration technology landscape, how do you see AI and automation reshaping not just visa applications but the entire ecosystem of global mobility and talent migration?

We’re witnessing the early stages of a fundamental transformation in how global talent moves across borders, and AI is the catalyst driving this change. The current immigration system was designed for a world where information moved slowly and decisions were made manually. Today’s reality demands systems that can process information at scale and accommodate the fluid nature of global talent markets.

In the next five to ten years, I expect AI-powered platforms to emerge across the entire immigration lifecycle. Beyond visa applications, we’re already seeing innovations in immigrant integration services, compliance monitoring, and talent matching between immigrants and employers. AI will enable more sophisticated matching algorithms that connect global talent with opportunities based not just on skills, but on cultural fit, long-term career goals, and optimal geographic placement.

The implications extend to how countries compete for talent. Nations with more efficient, transparent, and accessible immigration processes will gain significant advantages in attracting the world’s best minds. We’re already seeing countries like Canada and Australia investing heavily in digital immigration infrastructure.

AI will also enable more nuanced evaluation of candidates. Traditional immigration systems often struggle with recognizing diverse forms of achievement. AI can analyze patterns across massive datasets to identify talented individuals who might be overlooked by conventional criteria.

However, this technological transformation must be balanced with human values and ethical considerations. The most successful AI immigration systems will enhance human judgment rather than replacing it, ensuring technological efficiency serves broader humanitarian goals.

9) For entrepreneurs and highly skilled professionals currently navigating the immigration system, what are the key lessons you’ve learned about building successful immigration strategies, and what critical mistakes should they avoid?

The most important lesson I’ve learned is that immigration success requires strategic thinking and long-term planning, not just meeting minimum requirements. Too many extraordinary individuals approach immigration reactively, only considering their options when facing immediate deadlines. The most successful cases involve people who think strategically about their immigration journey from early in their careers, systematically building evidence and achievements that support strong applications.

One critical insight is understanding that immigration officers evaluate the totality of your case, not individual achievements in isolation. A startup founder with patents, media coverage, and industry speaking engagements can build compelling cases even without traditional academic publications. The key is understanding which types of evidence carry the most weight for your specific field and presenting that evidence coherently.

Documentation is crucial, but many applicants focus on quantity over quality. I’ve seen applications with hundreds of documents that tell no coherent story, versus applications with carefully selected evidence that builds a compelling narrative.

The biggest mistake I see is underestimating the importance of expert guidance early in the process. Many people spend months preparing applications independently, only to discover fundamental flaws that could have been avoided with proper guidance.

Another common error is failing to understand the specific requirements of different immigration pathways. O-1A versus EB-1A have different standards, and even different USCIS service centers show variations in evaluation approaches. Don’t let perfect be the enemy of good. If you meet qualifications, apply strategically rather than waiting indefinitely.

10) What’s next for OpenSphere, and how do you envision the company’s role in shaping the future of immigration technology over the next five years?

OpenSphere is positioned to become the definitive platform for high-skilled immigration, but our vision extends far beyond just improving the current system. Over the next five years, we’re building toward a future where immigration decisions are data-driven, transparent, and optimized for both individual success and national benefit.

In the immediate term, we’re expanding our AI capabilities to cover additional visa categories and immigration pathways. While we’ve achieved strong success with O-1 visas, the same principles apply to EB-1 green cards, L-1 visas for multinational managers, and other high-skilled categories. We’re also developing tools for immigration compliance, helping employers navigate the complex requirements of sponsoring international talent while ensuring they remain compliant with evolving regulations.

Our technology roadmap includes some exciting innovations in applicant evaluation and matching. We’re developing AI that can predict not just immigration success but long-term career outcomes, helping both individuals and employers make better decisions about immigration investments. This includes analyzing factors like cultural fit, career trajectory optimization, and geographic placement strategies that maximize both individual and societal benefits.

The data insights we’re generating will become increasingly valuable for policy development and strategic planning. We’re building anonymized datasets that could help policymakers understand talent flows, identify policy inefficiencies, and optimize immigration systems for economic growth. This positions OpenSphere as not just a service provider but as a thought leader in evidence-based immigration policy.

Internationally, we see opportunities to expand our platform to other countries facing similar talent competition challenges. The principles we’ve developed for the U.S. system apply broadly to other merit-based immigration programs, and we’re exploring partnerships with government agencies and international organizations interested in modernizing their immigration infrastructure.

Perhaps most importantly, we’re working toward a future where immigration becomes a positive, empowering experience rather than a source of stress and uncertainty. We envision a world where talented individuals can focus on their contributions to society rather than navigating bureaucratic complexity, where employers can efficiently access global talent, and where countries can make data-driven decisions about immigration policy.

Our ultimate goal is to help create an immigration system that truly serves its intended purpose: attracting the world’s best talent to contribute to American innovation, economic growth, and societal progress. Through technology, transparency, and strategic thinking, we believe we can transform immigration from a barrier into a bridge – connecting global talent with American opportunity in ways that benefit everyone involved.

The next five years will be transformative for immigration technology, and OpenSphere intends to lead that transformation while never losing sight of the human element that makes immigration so fundamentally important to individual lives and national success.