Precily’s text analysis engine powered by AI, NLP and deep learning modules is capable of analysing business documents, legal documents, research papers and others
Indian lawyers and chartered accountants are still reluctant to adopt AI solutions due to the fear of automation taking jobs away from humans and poor experience with legal technology in the past
Backed by legal-tech focussed investors like Pune-based VC firm Windrose Capital and Palo Alto-based law firm Inventus Law, Precily claims to have reached $1.8 Mn in ARR this year
In a typical law firm, there’s usually a whole lot of activity and perhaps twice as much paperwork. Traditionally, when an attorney prepares a document, it takes about 16 to 20 hours in gathering the data and looking into historical cases that are available on the internet and external data repositories. Once collected, preparing the document takes about one hour. After this, it is then vetted by subject matter experts or chartered accountants or lawyers etc, where the first pass-review accuracy is somewhere around 60-65%.
Further, due to supply-side inefficiencies, 80% of the tax and legal function’s time is spent gathering data and 20% analysing it, which directly impacts the bottom line of the business.
Indian lawyers and chartered accountants are still reluctant to adopt AI and automation due to ethical concerns, the fear of losing jobs to machines and past experience of technology that overpromised but underdelivered. While tech solutions have focussed on data discovery, search and analysis level, and very little has been done in successfully automating the documentation process. Besides Precily, some of the AI-focussed legal-tech startups in the country also include Volody, One Delta, SpotDraft, CaseMine, CaseIQ, Pensieve, and Practice League among others.
Legal tech startup Precily’s Bharath Rao recalls that five years ago there was this huge fear around automation tools reducing the billable hours for legal firms, which had a direct impact on their revenue.
At present, Precily claims to help its clients achieve more than 305% in revenue. Rao said that tax and legal firms are facing both supply and demand level pressures on productivity. Precily claims a first pass-review accuracy level of 92%. Pass-review or pass-in-review is a process of inspecting a document multiple times by various authorities or senior lawyers, before the draft or submission is finalised.
Now with Covid-19 in the picture, Rao, founder of Precily, a legal and compliance automation platform, believes that customers are becoming more responsive to technology that has immediate measurable financial benefits in terms of both cost-savings and opening up new revenue streams.
Rao said that the legal professional services industry alone is a $1 Tn opportunity and with average tech spend of 5% and one-third of tech spend expected on AI/ML platforms. “We see AI-led legal-tech opportunities between $15 to $20 Bn,” he added.
Tax and auditing firms across the globe are waking up to a new reality where artificial intelligence (AI) is taking over. Nearly 45% of companies in the US and UK are thinking of delegating audit/tax work to technology firms instead of traditional audit and legal firms. At the same time, the Big 4 (Deloitte, Ernst & Young, KPMG and PricewaterhouseCoopers) have also committed $9 Bn to AI spending in 2019. However, in India, only 4% of Indian lawyers are said to use AI capabilities in their operations.
While there are multiple legal-tech startups mushrooming in the space claiming to automate the redundant process for businesses, legal and auditing firms in India, they still lack the widespread impact or do not effectively address the issues that come up in terms of business outcomes, Rao added.
The Journey Of Automating Tax & Legal Workflow
In simple terms, Precily AI is a text analysis tool powered by AI, NLP and deep learning modules, where its engine is capable of analysing business documents, legal documents, research papers and others.
Founded in 2018 by Rao, Precily began its journey by summarising tax and legal documents in the initial years. With time, the company started spreading its roots in assessing tax and legal data to assist subject matter experts for faster and more accurate analysis.
Recalling the early days, Rao told Inc42 that three years ago, without any prior tax and legal experience, he faced several challenges in terms of acquiring customers, validating the product and convincing large firms and the Big 4 consulting firms.
The focus was on strong product offering targeting a core workflow and bringing fundamental transformation or automation in the process. While it could not reveal the names of its clients due to confidentiality reasons, Rao said the company plans to add over 50 more customers by 2021.
Based in New Delhi and Palo Alto, California, Precily is currently focussed on the US and India market, but in the coming months, it is looking to expand its presence in Australia. Currently, it has a team of about 30 members, consisting of data scientists, engineers and subject matter experts (CA/CPAs and lawyers), and has also partnered with IIIT, Delhi to extend its research capabilities.
Backed by legal-tech focussed investors including Pune-based VC firm Windrose Capital and Palo Alto-based law firm Inventus Law, the company revealed that in 2020 it has reached $1.8 Mn in ARR, and is heavily investing in ramping up its team, product development and business expansion.
Impacting The Bottom Line
So how is the company able to achieve this level of accuracy? Explaining in simple terms, the founder of Precily citing the example of tax notice document preparation said that irrespective of the types, be it royalty, depreciation, capital gains etc.
At the paragraph level, based on the context the user is looking/searching for, its platform leverages natural language programming (NLP) where it is able to retrace information and find relevant data from the internal and the external data repositories within seconds and create a summary document, added Rao.
It was easier said than done, Precily’s Rao stated:
“As we wanted to give our customers a near do-it-yourself (DIY) AI platform that can be ubiquitous to multiple practice areas of law and tax advisory firms, quickly training data and expanding to adjacent use-cases within tax and legal was an initial challenge.”
However, the company said that it was able to achieve this through automated learning platforms and data training models which are built grounds up for law firms and legal workflows, thus ensuring the platform’s learning and deployment cycle is far shorter for other adjacent use-cases in any legal domains.
Being a vertical SaaS platform that is targeting legal firms, Precily follows a guaranteed commitment or retainer model ranging from $500K to $1 Mn per customer, besides a subscription model at $50 per user per month, limited to 50 users per company.
The platform has the capabilities of doing entity extraction, sentiment analysis, text clustering, concept extraction, custom tag summarisation, comparing multiple documents and extracting relevant information and eliminating repeated content, thereby creating a summary of the major points of the original document. Also, its AI platform has the capabilities to make a coherent summary taking into account variables such as length, writing style and syntax etc.
“The learning platform (Precily Aura) that we have developed actually helps our customers target each and every practice area within the tax and legal firms, keeping research and analysis at its core. Most importantly, help them focus on higher cognitive tasks,” added Rao.