Compliant AI

Co-Founder

Modulos AG

AI, Data Privacy and Tech

Lano

General Counsel

Code Arm

Legal Advisor

PurpleRain Technologies Inc.

Technik

Advised on matters related to employees law, IP, tech law, compliance and finance law

Law⚖️ and Technology💻

I'm a qualified lawyer with over 12 years of experience at the intersection of technology, data privacy, and commercial law. Over the past decade, I’ve built deep expertise advising on cutting-edge legal issues related to artificial intelligence, cybersecurity, remote work, blockchain, digital assets, and regulatory compliance across multiple jurisdictions.

My work spans:

* AI and emerging technologies
* Data privacy and cybersecurity
* IP and commercial contracts
* Employment law and international expansion
* Labour and regulatory compliance
* Financial and banking law
* Virtual assets and blockchain

Recognized as one of Asia’s Top Legal Innovators (2021 & 2022) and among the Top Women Legal Innovators globally (2021 & 2022), I bring a forward-thinking, practical approach to solving legal challenges in fast-evolving sectors.

Beyond my legal practice, I’m deeply passionate about the environment, wildlife, and climate action, and actively volunteer with aligned communities.

**Views expressed are my own.**




I'm excited to start my new role as Lead Counsel - AI Risk and Compliance at Predixtions Inc. 

Life seems to come to a full circle with this role for me - back to the intersection of #law, #AI, #privacy, #IP and #product. 

I will be working on TrustModel AI and all sections around #AI development and #AIgovernance.

Thanks for the opportunity Karl Mehta!

If you are building, deploying and/or working with #AIsystems, check out TrustModel AI!

Bhagyashree Pancholy

#NGT started with colour and brought in a green legal revolution - the initial years, it had enormous power which it exercised freely and often, albeit unapologetically. Now, it is becoming colourless and dying. Look at the Nicobar Project case.

I have seen NGT benches since then rendering "profuse apology" in one of the cases of the organization I volunteer with because a certain Supreme Court judge had written to the judicial member for undue intervention. Interestingly, the matter was already transferred to the NGT by another SC bench, but the said judge was unaware (and why, bothered?). 

The asymmetrical approach of the NGT is worrying. As pointed out, clearances often do no follow due procedures, esp Forest Clearances and Environmental Clearances. What is the point of preservation of forests if it has to be cut for any trivial project?

Another interesting point that I have often challenged, while challenging the grant of a FC, is the grant of the clearance for ten years and subsequent non-renewal. Investment worth lakhs of crores to build a hydel power plant or a ropeway or any other work just for 10 years? What happens to that project after 10 years? More often then not, the project proponent files for a stay against non renewal in the 8th or 9th year and then it runs till eternity 😉

This is definitely not leading to any kind of development, let alone sustainable one.

#environment #forests #environmentallaw #law #litigation

A landmark 2021 judgment by the Supreme Court described the National Green Tribunal (NGT) as a “specialized” protector of environmental justice, tasked with safeguarding public interest against ecological degradation. But an investigation by The Indian Express of over 1 lakh NGT orders since 2020 points to a growing asymmetry in how the Tribunal has ruled on environmental and forest clearances.

Between 2020 and 2025, in appeals related to Environment Clearance (EC) and Forest Clearance (FC), the NGT ruled in favour of project developers in four out of five cases — either by upholding a contested clearance or staying its denial. Of the 329 appeals filed by citizens and activists against clearances granted by the government, only 20% (65 cases) succeeded. In contrast, when project proponents challenged the rejection or cancellation of clearances, they secured relief in nearly 80% (126 of 159 cases).

Data from 2016–2019 shows a more balanced trend, but the pro-project tilt has sharpened in the past two years. Between 2024 and 2025, only 7% of appeals challenging clearances were successful, while 88% of industry-led appeals against rejections got relief. A significant number of citizen appeals were dismissed as “time-barred” for missing the 90-day deadline, or rejected as “not tenable”.

Click on the 🔗 below to read the article.
https://lnkd.in/g38MF-Rs

green watchdog NGT rules

Yeap, we have seen it time and again. 

#un #internationallaw #law #worldwar #iran

AI Risk and Compliance Lead Counsel

When my employer TrustModel AI, shared our framework for #AIgovernance in hiring (you’ll see the full post and image below), I knew I had to share my own story about why this mission is deeply personal for me.

We are often taught to worship the optimal path - the linear career, the elite university, the perfectly uninterrupted upward trajectory. AI is excellent at finding this path. In fact, it is too good.

But from my perspective as both a human and an AI governance lawyer, my deepest concern is that in our obsession with "efficiency," we are engineering compassion right out of the workplace. We are quietly building a system that rewards the machine-like and punishes the human.

If my own journey has taught me anything, it's that human value isn't a single score, it’s a mosaic.

Here are the three truths I carry that shape our platform’s design:
💹  I choose survival over success - I have learned that the candidate with the 3-year "caregiving gap" on their resume often possesses more resilience, project management skill, and raw empathy than the Ivy League graduate who has never faced a pivot. A compassionate AI must be governed to see the strength in these "survival patterns."

😇 I believe in Algorithmic Forgiveness -  Who among us is the same person they were ten years ago? Five years ago? Human dignity requires that we have the right to evolve. An ungoverned AI has an infinite memory for our mistakes. True governance mandates that data recency is not a box to check, but a guardian of a person’s future.

❌  I know the ineffable cannot be automated. There is a subtle, beautiful intuition- a gut feeling - that a great leader has when they meet a candidate. It’s the meeting of human souls. To let an #AI reduce that human spark to a "0-to-1 score" is not optimization; it is the devaluation of what makes us human. 

We must govern AI to be a tool that supports, rather than replaces, human judgment. 

The resumes we reject often tell the most profound stories.

#hiring #hrtech #ATS #AIgovernance #AIbias #AIaudit #responsibleai #explainableai #dataaudit #data #aisystems

When we talk to #HRtech leaders about #AIgovernance, they often ask about risk mitigation or audit trails. 

But as the architects building the infrastructure to govern these systems, our concern is much deeper.

We are quietly building a hiring landscape that is perfectly efficient and completely devoid of human compassion.

If our clients don't bake human values into the very architecture of their #AI, they aren't just automating recruitment; they’re automating a compassion crisis.

Here are three reasons why we believe governance is a moral imperative, not just a legal one:

1. The Pattern of Survival vs. The Pattern of Success

Most AI models are trained to find success patterns: linear career paths and elite degrees. But we know that some of the most resilient, high-value humans have survival patterns. They have gaps for caregiving, unconventional pivots, or seasons of struggle. 

Our Platform’s Stance: Governance must force AI to recognize Socio-Economic Context. Without it, we aren't optimizing talent; we are systematically punishing human vulnerability.

2. The Algorithmic Permanent Record

Human compassion allows for the comeback story. We believe people grow. But an ungoverned AI has an infinite, cold memory. It can #shadowban a candidate for a data point from a decade ago, effectively stripping them of their right to evolve. 

Our Platform’s Stance: We need Algorithmic Forgiveness. Governance ensures that a person’s past, their data ghost, doesn't haunt their future indefinitely. A human life is a journey, not a static dataset.

3. The Standardization of the Soul
There is a profound danger in Quantifying the Ineffable. Grit, intuition, and heart cannot be reduced to a 0-to-1 score without losing what makes them valuable. When we let an ungoverned black box decide "culture fit," we are essentially saying that anything the machine can't measure doesn't exist. 

Our Platform’s Stance: Governance is the "Context Layer." It’s about creating Compliance-by-Design so that the final decision remains a qualitative, human judgment - preserving the dignity of the person behind the resume.

We didn't start an AI governance company to build a better "brake." We started it to build a better compass. We are at a crossroads where we must decide: will our technology serve our humanity, or will we force our humanity to bend to the technology? 

If you are using #AI to hire, do check out our platform.

#algorithmicbias #algorithimicbias

California's Civil Rights Council regulations on #AIhiring are in effect. I am surprised that I did not see many talk about it or even ask about it, especially when so many #AI and #hiring companies are active or based in California.

Anyhow, these regulations mandate #AIgovernance and explainability. The lengthy contracts are no longer a defense shield. It is explainability and documentation with evidence.

Platforms like TrustModel ensure that AI governance is no longer just about ethics, it’s about litigation readiness. Companies that can prove they have a "human-in-the-loop" and a rigorous audit trail will be the ones that thrive under this new regime.

🚨 California’s October 1st AI Deadline is Here: Is Your Governance "Defensible"?

With the final approval of California’s Civil Rights Council regulations, the era of “experimental” AI in hiring is officially over. 

As of October 1st, 2025, employers are strictly liable for the algorithms they use - even those provided by third-party vendors.

The question isn't just if you use AI, but how you govern it. This is where an AI Governance platform like TrustModel transforms from a tool into a legal shield.

How TrustModel Solves the California Compliance Gap:

1. Automated Anti-Bias Audits (The "Affirmative Defense") 🛡️
California law now lists "proactive anti-bias testing" as a key factor in your legal defense.

2. Vendor Risk Management (The "Agent" Liability) 🤝
The new regulations state that you are liable for your vendors' AI. You can no longer outsource your responsibility.

3. The 4-Year "Decision Log" (Record Keeping) 📂
Data retention requirements have doubled to four years. If a candidate sues in 2028 for a decision made today, you need the receipts.

4. Disability & Medical Inquiry Guardrails ♿
The law now scrutinizes AI that measures physical or behavioral traits (facial expressions, reaction times) which could inadvertently screen out people with disabilities.

The platform helps map AI assessments against accessibility requirements, alerting HR teams when a tool’s measurement technique may cross into "unlawful medical inquiry" territory, allowing for timely human intervention.

The Consequences of "DIY" Governance:
Without a dedicated platform, you are betting your company’s reputation on manual spreadsheets and vendor promises. 

The risks include:
Strict Liability for biased outputs you didn't even know were happening.
Massive Litigation due to a lack of an audit trail.

Algorithmic "Stop Orders" from the Civil Rights Department that can freeze your hiring overnight.

California is setting the global standard. Efficiency is great, but Defensibility is the new ROI.
Is your tech stack ready for October 1st? See how TrustModel can automate your compliance journey.

#AIGovernance #TrustModel #CaliforniaLaw #HRCompliance #EthicalAI #RecruitmentTech #LegalTech #AIHiring

108 days in jail because of a "false positive."

Efficiency should never come at the cost of fundamental rights.

This story is a devastating example of why #AIGovernance isn't just a compliance checkbox - it’s a civil rights necessity. When facial recognition software is used without rigorous human-in-the-loop verification, the consequences aren't just technical errors; they are human tragedies.

#law #fundamentalrights #llm #aisystems #biometrics #ai

Imagine being arrested at gunpoint while babysitting your grandkids, extradited 1,200 miles away to a state you’ve never even visited, and spending six months in jail - all because an AI facial recognition tool made a "match."

Angela Lipps, a Tennessee grandmother whose life was upended by a North Dakota bank fraud case she had nothing to do with.

While she was behind bars, she lost her home, her car, and even her dog. The case was only dismissed when her lawyer provided simple bank records proving she was in Tennessee during the crimes.

Why does this happen? 

It’s a failure of #AIGovernance and human oversight.

As we integrate AI into critical public infrastructure like policing, we must move beyond the "black box" and implement rigorous guardrails:

✅ Human-in-the-Loop is Mandatory: AI should be a tool for lead generation, never the sole basis for a deprivation of liberty. Algorithms provide probabilities, not certainties.

✅ Bias & Accuracy Accountability: We know facial recognition often struggles with diverse demographics. Without transparent audits and strict accuracy standards, these tools become "bias-amplifiers."

✅ The Duty of Verification: Governance isn't just about the code; it’s about the process. When an AI flags a suspect, the human "check" must be more than a cursory glance at a driver's license photo.

✅ Redress & Remediation: Effective governance must include clear protocols for when things go wrong. In this case, the lack of an apology or assistance for an innocent woman stranded 1,200 miles from home is a secondary systemic failure.

Innovation without ethics is a liability. As leaders in tech and policy, we have a responsibility to ensure that "efficiency" never comes at the cost of fundamental human rights.

We need robust #AI legislation and internal corporate governance that treats "false positives" not as statistics, but as human lives.

#banking #aisystems #llm #ailaw #aibias #aiaudit

As someone who has navigated the intersection of tech #law, #HRTech, and #AI risk for over a decade, I’m seeing this friction point firsthand. Investors are no longer satisfied with high-level ethical frameworks. 

They are demanding granular, auditable evidence of Explainable AI (#XAI) and real-time risk mitigation.

At TrustModel.ai, we’re helping boards move past the black box era. If you can’t point to your data lineage or prove your Human-in-the-Loop protocols, you aren't just facing a compliance hurdle-you’re sitting on unmanaged enterprise risk.

A robust governance layer is your new "Trust Moat."

Why this matters for your next round:
✅ Investor Scrutiny: Due diligence now requires hard evidence of algorithmic auditing and bias prevention.

✅ Vendor Transparency: You are only as compliant as your weakest AI vendor. Transparency must be end-to-end.

✅ Regulatory Reality: With the EU AI Act and local laws maturing, "static policies" are liabilities. You need active monitoring.

We are moving into a landscape where transparency is the ultimate competitive advantage. It’s time to stop treating governance as a check-the-box exercise and start treating it as a core pillar of product architecture.

#AIGovernance #AIRisk #TechLaw #ComplianceByDesign #TrustModel #VentureCapital #ResponsibleAI #productmanagement

While many tech-heavy companies have opened their governance structures, the quality of information remains a major point of friction. 

In 2026, the era of "Trust us, we’re ethical" is over.

At TrustModel.ai, we are seeing a significant shift in the legal landscape: a surge in shareholder resolutions asking for hard evidence, not just high-level principles. Investors are now demanding granular disclosure around:

⚠️ AI Guardrails: Real-time monitoring and intervention protocols that prevent model drift and hallucinations.

⚠️ Data Sourcing & Lineage: Absolute transparency on the provenance and intellectual property rights of training sets.

⚠️ Human-Rights Assessments: Concrete, auditable evaluations of how automated systems impact privacy, labor, and systemic bias.

For boards and executive leadership, this is no longer a nice-to-have CSR initiative, it is a fiduciary requirement. If you cannot demonstrate your guardrails, you cannot prove you are managing enterprise risk.

The Solution? 

Move from static policies to an active Governance Layer. A robust AI governance platform doesn't just "check a box"; it creates a "Trust Moat" by providing the auditable trail that regulators and institutional investors now expect as a baseline.

The companies that win in the #AI economy will be those that turn transparency into a competitive advantage.

#aigovernance #csr #risk #compliance #agm #investors

If you’re moving past the "AI hype" and into actual deployment, this new report from #NIST (AI 800-4) is a must-read. 🛡️

The biggest takeaway for me? Pre-release testing is no longer enough. AI is non-deterministic - it behaves differently in the "wild" than it does in a lab. Real governance means moving from a "ship and forget" mindset to continuous monitoring.

NIST breaks it down into 6 areas we need to track: 
1️⃣ Functionality: Is the model drifting? 
2️⃣ Security: Are we protected against "deceptive" AI behavior? 
3️⃣ Human Factors: Is it actually helpful and transparent to users? 
4️⃣ Compliance: Are we meeting global standards? 
5️⃣ Operational: Is the infrastructure holding up? 
6️⃣ Impact: Is it actually contributing to human flourishing?

AI governance isn't just about "playing it safe"; it’s about building systems that stay reliable and trustworthy long after the launch button is pressed.

 📉👇
#AIGovernance #NIST #ResponsibleAI #TechLeadership #AI #AIlaw

The NIST AI 800-4 report, titled "Challenges to the Monitoring of Deployed AI Systems," underscores a critical shift in the industry: pre-deployment testing is no longer enough. Because AI is non-deterministic and behaves differently in the "wild" than in a lab, continuous governance is the only way to ensure safety and performance.

If you think your AI is safe just because it passed pre-release testing, the latest report from NIST (NIST AI 800-4) has a wake-up call for you.

AI systems are non-deterministic. They evolve. They drift. They encounter real-world scenarios that no lab environment can fully simulate. This is why AI Governance - specifically post-deployment monitoring -is no longer "nice to have." It is a business imperative.

According to the NIST Center for AI Standards and Innovation (CAISI), effective governance requires monitoring across six critical pillars:
✅ Functionality: Is the model still accurate, or has its performance degraded over time? 
✅ Security: How do we detect "deceptive behavior" where a model might hide its true capabilities under evaluation?
 ✅ Human Factors: Are the outputs actually high-quality and transparent to the end-user?
 ✅ Compliance: Are we keeping up with a "complex and heterogeneous" global policy landscape?
 ✅ Operational: Is the underlying infrastructure reliable at scale? 
✅ Large-Scale Impact: Is the system truly promoting human flourishing, or is it causing subtle, distributed harms?

Building great AI is only half the battle. Governing it in the real world is where the true leaders will be defined.

Are you monitoring your AI after it's live? Or are you flying blind? ☁️ Link to the report in the comments 👇 

#AIGovernance #NIST #ResponsibleAI #MachineLearning #TechLeadership #AIsafety

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