UK-headquartered startup Wexler uses large language models to help lawyers (and eventually consumers) extract and organise key data from documents relevant to their case. Here the founders give us all their vital statistics, from how the platform works, to who their key execs are, and what funding they have received to date.
How would you describe your company to a friend?
Wexler is the AI copilot for every legal dispute. We are building a suite of products to help litigators at firms, in house counsel, SMEs and in time, consumers extract and organise the key facts related to their case, saving critical time and ultimately helping them win more cases.
Our first product is a chronology builder for these teams, helping disputes lawyers to reduce write offs and improve outcomes by building accurate and comprehensive chronologies from the disclosed documents in their cases.
And if you had to describe it to a techy?
Wexler harnesses LLM technology into a series of workflow products which help litigators win more cases.
By extracting, classifying and ordering key facts from the enormous volume of documents related to a case, Wexler helps lawyers conduct deep factual and legal analysis of each matter, so they can construct the story of their cases.
With Wexler, litigators constantly refer back to the evidence at every stage of their dispute.
When were you founded?
We were founded in January 2023 on the Entrepreneur First LD19 Cohort.
Gregory Mostyn and Kush Madlani.
Gregory is a Sales and Marketing leader with 6+ years running commercial teams at VC backed startups. He has grown up in a legal family, with his father Nicholas a (recently retired) HC judge in the family division having long been an advocate for law reform. Throughout his life he has been imbued with the passionate beliefs of his father about the deficiencies in the system and the reforms that are necessary.
Kush is an AI expert with an academic and professional background in Machine Learning. An ex-Tractable ML Researcher, he left his career as a derivatives trader after teaching himself how to code. He learned how to build world class applied AI products and teams at Europe’s first computer vision unicorn with the aim of becoming an entrepreneur.
Who are your key managers/senior execs?
The rest of the team is loaded with experience building world-class applied AI products to disrupt legacy industries. Significant experience handling and cleaning real world data, solving human tasks at HLP, creating knowledge graphs and building enterprise software products with extremely high ACVs.
What is your growth strategy?
Outbound through our extensive network to launch POCs with innovative city firms in the UK and global firms in the US, paired with an inbound motion based on social proof, testimonials and content marketing.
We adopt a land and expand strategy to shorten sales cycles, before growing within firms as more disputes, investigations and litigation teams are onboarded.
Have you received investment?
We have recently a £400k pre-seed round with participation from key business angels including Charlie Delingpole and Nickyl Raithatha, scouts from Accel, Atomico and Index and two investment syndicates.
Who are your target clients?
We target innovative BigLaw firms with significant disputes, investigations or white collar crime teams, in the UK, Europe, Australia and the US. We also sell to in house teams who regularly deal with litigation.
Have there been any key changes in direction since you were founded?
We first launched a knowledge management tool to summarise judgments in the England and Wales Courts, which we still offer as part of our product.
After speaking with our customers, we decided to accelerate the development of our litigation copilot to increase our market size beyond knowledge management & support lawyers and assist litigators with developing the spine of their cases – the chronology.
What are the key challenges you face in your market?
The perennial challenge with selling to Enterprise law firms are the length sales cycles. It is essential to build relationships with your customers, visit them in person as much as possible and try to template as much as possible regarding contracts and MSAs. AI is forcing firms to act faster than they ever have before, meaning that there is a significant tailwind to push through the longer sales cycles involved in selling to large firms.
What are the most exciting developments you’ve seen in your market in the past year for the past year to 18 months?
No prizes for guessing… LLM technology & ChatGPT have opened lawyers eyes to a revolution in the industry.
Firms know they have to engage with the tech to avoid being left behind, and the lawyers themselves are stunned at the proficiency of large language models in performing routine legal tasks.
The key going forward will be separating the products that actually solve key problems for users and those which promise the world and deliver little of value.
Tell us something that people don’t already know about the company?
We are named after Kim Wexler, of Better Call Saul fame!