Marketing Manager

𝑫𝒐 𝒚𝒐𝒖 𝒌𝒏𝒐𝒘 𝒚𝒐𝒖 𝒄𝒂𝒏 𝒈𝒆𝒏𝒆𝒓𝒂𝒕𝒆 𝒓𝒆𝒗𝒆𝒏𝒖𝒆 𝒕𝒉𝒓𝒐𝒖𝒈𝒉 𝑳𝒊𝒏𝒌𝒆𝒅𝒊𝒏 for your business but are you struggling with 𝑳𝒊𝒏𝒌𝒆𝒅𝒊𝒏 𝑺𝒕𝒓𝒂𝒕𝒆𝒈𝒚 𝒂𝒏𝒅 𝑴𝒂𝒓𝒌𝒆𝒕𝒊𝒏𝒈? Well, that's where I come in.



𝑰 𝒉𝒆𝒍𝒑 𝒚𝒐𝒖 𝒖𝒔𝒆 𝑳𝒊𝒏𝒌𝒆𝒅𝒊𝒏 𝒕𝒐:-

1. Generate organic leads and convert them.

2. Make your target market see you as an expert in your industry.

3. Make your target market know about your brand as well as increase your revenue.

Do you want to get heard by millions of your target market, then this platform will be a gold mine.




𝑫𝒎 𝒎𝒆 𝒐𝒏 𝑳𝒊𝒏𝒌𝒆𝒅𝒊𝒏.

Venkat Pagilla

Chair @ Deel Lab | Building Legal AI l Driving Global Work Policy

I lead the Conflict Analytics Lab (CAL), a frontier AI research lab focused on law and dispute resolution. Our work examines how advanced AI—especially reasoning systems—can support access to justice and improve legal decision-making. A central part of this research explores how lawyers and AI can co-design reliable legal technologies.

I also founded OpenJustice, an open-source platform spun out of the Conflict Analytics Lab. Using a no-code method, lawyers encode structured logic, constraints, and experiential knowledge directly into AI systems. The aim is to reduce hallucination and sycophancy by adding reasoning layers—not more data—thereby improving reliability, alignment, and performance in high-stakes legal tasks.

Previously, I served as Chief of Policy and Head of the Deel Lab at Deel, where I led the development of several applied AI projects, including the Deel AI Classifier. I am an Associate Professor at Queen’s University Faculty of Law, with visiting faculty appointments at Cornell University and Paris Dauphine University, and past academic affiliations with ENA and Harvard University.

Earlier in my career, I served as a Cabinet Member at the Court of Justice of the European Union, advised the European Commission on financial aid programs in Eastern Europe, and worked as a conflict resolution consultant at IRENE–ESSEC. I also clerked for the French Administrative Supreme Court (Conseil d’État).

Samuel Dahan

💯  agree but I don’t think Canada has an AI talent problem.

We have a follow-through problem.

Yes, students should stay in Canada. Our research system is strong, and there are many ways to build excellent labs and teams here - thanks to Natural Sciences and Engineering Research Council of Canada (NSERC) Mitacs  Social Sciences and Humanities Research Council of Canada (SSHRC) and many others

But the real is issuse: research happens in Canada → value creation happens elsewhere and it gets funded well.

US capital comes in, turns research into global industries — and often relocates the companies.

The impact is real, which is good.

But too often, the long-term benefits aren’t captured in Canada.
That’s not sustainable.

If we want people to stay, we need to make it easier to build, deploy, and scale research in Canada — not just publish it.


Minister Evan Solomon 
https://lnkd.in/ejqFb26E

Building Data infrastructure for Legal AI | Co-founder, OpenJustice | Law Professor | MILA

The Globe and Mail on Canada’s “legal data desert” — out today

 An investigation by Robyn Doolittle, published this morning, looks at a quiet but serious issue in Canada’s justice system:

We don’t have a complete, public record of court decisions.
Here’s why that matters.

In Canada:
- judges decide what gets published
- courts voluntarily send decisions to CanLII
- some decisions go to commercial databases
- many never become easily accessible at all

There is no centralized, public system that guarantees full access.

CanLII does important, open-access work — and deserves credit for it.

But public legal data is still fragmented and not open for bulk access.

That creates two downstream problems.

First: AI becomes winner-takes-all.
Without bulk legal data, only a few actors can build serious legal AI tools. Less competition → very expensive products → limited access for legal aid orgs and solo practitioners — often the people who need these tools most.

Second (and deeper): you can’t evaluate justice without the full picture.
If we can’t see all decisions, we can’t tell whether similar cases are decided consistently.

Inconsistency doesn’t disappear — it just becomes invisible.

Other countries have moved differently (France, the UK, the U.S.).
- with Free Law Project Michael Lissner in the US; #Judilibre Édouard Rottier ; #CambridgeLegalCorpus Felix Steffek

Canada is increasingly an outlier 

This isn’t just a tech issue.

It’s about transparency, accountability, and the rule of law in a digital age.

This raises a bigger question:
Can we really talk about access to justice if we can’t fully see how justice is applied?

https://lnkd.in/e6xU8nb3

There’s a lot of enthusiasm right now around agentic systems and “#vibecoded” AI - even in LAW

And rightly so — they’re fast, creative, and often impressive.

But this image (below) captures something lawyers should pause on.
In legal AI, the real risk isn’t messy code.

It’s deploying uncertain legal outputs at scale.

Agentic systems are, at heart, a form of output deployment.
 If the underlying legal reasoning is inaccurate or only partially correct, agents don’t fix that.

They replicate it, route it, and embed it into workflows — where mistakes become harder to detect, harder to explain, and harder to unwind.

That dynamic feels uncomfortably familiar.

A bit like 2008:
opaque products
layered delegation
errors passed quietly from system to system
until no one can clearly trace where the problem started
Agents are powerful.

But in high-stakes domains like law, speed is not the binding constraint.
Substance is.

We’re still seeing error rates north of ~50–60% in many legal RAG setups.
 Scaling that through agents doesn’t create leverage.
It creates systemic risk.

For law firms and legal institutions, the priority should be:
getting the legal content right
making reasoning inspectable and traceable
then deploying agents on top of something lawyers can actually stand behind

Agents will matter. A lot.
But first we need to scale correctness, not confidence.
—
Image and original framing inspired by a post from Andreas Horn.
his newsletter: 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://lnkd.in/dbf74Y9E


#LegalAI #AgenticAI #ResponsibleAI
#vibeCoding

Another reason for Canada to build its own deep-tech investment system

With Y Combinator stepping back from Canada, it’s a reminder that foreign capital doesn’t always align with where value is built long-term.

The flip side is encouraging. As #MarkCarney noted at World Economic Forum, Canada has capital, talent, strong pension funds, and a very competitive environment for investment.
 
The opportunity: public capital, pensions, and private investors (both Canadian and Foreign) working together to anchor pre-seed and seed funding for deep tech and research-driven companies in Canada

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Venkat Pagilla

Samuel Dahan

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The Battle

Venkat Pagilla

Samuel Dahan

Followers

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Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Samuel Dahan's LinkedIn Performance

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