Startup Deep Dive : Skit.ai — Raised a $23 million Series B led by WestBridge Capital in September 2021

Skit.ai (formerly Vernacular.ai, legal name Cyllid Technologies Private Limited) is a voice AI company founded in 2016, based in Bengaluru with a New York headquarters, focused on automating call-centre conversations, especially debt collection.

This Startup Deep Dive explains what Skit.ai does, how it makes money, who backs it, how it compares with rivals and what could go wrong, using publicly available information. It is educational and not investment advice. Last updated: October 2026.

Skit.ai in Brief

  • What it is: Skit.ai is an Indian Voice AI company based in Bengaluru (new headquarters in New York per 2021 coverage).
  • Who it serves: businesses, institutions, consumers, learners and public-sector buyers.
  • Sells VIVA (Vernacular Intelligent Voice Assistant), an AI voice automation platform based on natural language understanding.
  • Supports 16+ languages and 160 dialects.
  • Focuses on accounts receivable and debt collection (first and third party collections).
  • Funding: Reports differ: about $28 million to $53 million; TechCrunch said $30 million as of 2021.

Skit.ai Quick Facts

Company Skit.ai
Founded 2016
Headquarters Bengaluru (new headquarters in New York per 2021 coverage)
Founders Sourabh Gupta, Akshay Deshraj
Sector Voice AI
Total funding Reports differ: about $28 million to $53 million; TechCrunch said $30 million as of 2021
Latest round $23 million Series B, 2021, led by WestBridge Capital
Valuation Not disclosed
Website Not disclosed

Figures marked “reported” come from published reports and may differ between sources; “Not disclosed” means no reliable public figure was found.

What Is Skit.ai?

Skit.ai operates in the Voice AI space in India. Understanding a company like this starts with three questions: who is the customer, what painful problem is being solved, and why the solution is better than the alternatives. The sections below apply that lens to Skit.ai.

  • Sells VIVA (Vernacular Intelligent Voice Assistant), an AI voice automation platform based on natural language understanding.
  • Supports 16+ languages and 160 dialects.
  • Focuses on accounts receivable and debt collection (first and third party collections).
  • Had 25+ B2B clients in 2021 including Axis Bank, Hathway, Porter and Barbeque Nation.

The Origin Story of Skit.ai

Every company starts from a noticed gap and a team willing to commit to closing it. Strong origin stories are specific: a clear problem, a founding team with relevant skills, and an early product that real customers could test. Founder-market fit, meaning the team’s lived experience or technical depth in the domain, tends to predict how fast a young company learns.

  • Founders: Sourabh Gupta, Akshay Deshraj.
  • Founded in 2016 as Vernacular.ai by IIT Roorkee alumnus Sourabh Gupta and Akshay Deshraj.
  • Later renamed Skit.ai and moved focus toward the US collections market.

Key Milestones and Challenges

No startup grows in a straight line. Early years usually involve slow adoption, product rewrites, hiring mistakes and funding gaps. In the Voice AI sector the common turning points are a first paying customer, a regulatory approval, a successful product demonstration or a funding round that lets the team invest ahead of demand. How a team responds to setbacks says more about resilience than any single headline.

  • 2016: Founded.
  • May 2020: $5.1 million Series A.
  • 2021: Quadrupled revenue and customer count between 2020 and 2021 (company claim).
  • September 2021: $23 million Series B led by WestBridge Capital; about 150 employees.

Skit.ai Funding and Investors

Funding history shows how much outside confidence a company has attracted and how long it can operate before needing more capital. Figures below are reported and may differ between sources; valuation figures are estimates unless the company has confirmed them.

  • 2017: Seed round listed by one database (amount not given).
  • May 2020: $5.1 million Series A.
  • September 2021: $23 million Series B led by WestBridge Capital with Kalaari Capital, Exfinity Ventures, IAN Fund, LetsVenture, Sense AI and an angel investor.

How Does Skit.ai Make Money? (Business Model)

A business model describes who pays, how often and how much it costs to serve them. Strong models show repeat usage, improving margins with scale and acquisition channels that do not depend only on paid spend. Weak models show one-off sales, rising costs and growth that stops when spending stops. For companies selling to businesses, institutions, consumers, learners and public-sector buyers, sales cycles and contract size matter as much as headline growth.

  • Subscription-based AI-as-a-service sold to enterprises and collection agencies.

The Numbers: Skit.ai Financials

Financial figures show whether growth is turning into a self-sustaining business. Small and private companies often disclose little, so any number below is included only if it was found in public reporting.

  • FY24: revenue Rs 28.4 crore; loss Rs 78.2 crore; expenses Rs 106.6 crore (Inc42).
  • FY25: revenue Rs 52.1 crore (up 83%); loss about Rs 0.42 crore (Inc42 main table); the same page's FAQ gives revenue Rs 43.5 crore and loss Rs 36.7 crore, so reports differ.

Market Opportunity for Skit.ai

Market size is easy to exaggerate, so a useful approach separates the total market from the portion a company can realistically reach with its current product and distribution. The main forces behind demand in this sector are rising digital adoption, cloud and mobile penetration, growing enterprise technology spending, government digitisation programmes and a deep pool of engineering talent. Each of these widens the opportunity, but capital efficiency and execution decide who captures it.

  • Voice automation for BFSI, collections, logistics and e-commerce.

Technology and Product at Skit.ai

Technology is rarely the whole moat, but it drives speed, cost and customer experience. A practical way to assess it is to separate the capability the company controls from the commodity infrastructure it rents. In this sector the important factors are product quality, data and integration depth, security, scalability and the speed of shipping improvements.

  • NLU-based voice assistant working across many Indian and English dialects.

Team and Culture at Skit.ai

Teams are the most important and least measurable asset of a young company. Look at how complementary the founders’ skills are, how deep the second layer of leadership is, and how the company hires and retains specialists. Culture shows up in small repeated behaviours: how quickly bad news travels upward and whether commitments to customers are kept.

  • Sourabh Gupta is co-founder and CEO.
  • About 150 employees in 2021.

Skit.ai Competitors: Competitive Landscape

A fair competitive analysis names direct rivals, adjacent players who could move into the space, and the customer’s default alternative. Durable advantages include proprietary data or technology, licences and approvals, brand trust, switching costs and cost leadership.

Competitor How it differs
Observe.ai Named by one source.
Yellow.ai Named by one source.
Gnani Named by one source.
Vodex Voice solutions for debt collection, named by one source.

Risks and Challenges for Skit.ai

  • Large losses in FY24 relative to revenue.
  • Competition from other voice AI vendors.
  • Source data on financials conflicts.
  • Competition: low barriers to entry and well-funded rivals can compress pricing and slow growth.
  • Funding risk: technology businesses often burn cash before reaching profit and depend on investor appetite.

Risk is not a reason to avoid a company; it is a reason to price it correctly and to monitor the right indicators over time. Regulation in this sector is shaped by data protection rules under the Digital Personal Data Protection Act, sector regulators, consumer protection law and IT rules.

Skit.ai Growth Outlook: What to Watch

  • FY25 data suggests losses narrowed sharply as expenses fell about 51% (Inc42).
  • Key indicators: recurring revenue, customer retention, gross margin, customer acquisition cost and runway.
  • Funding position: Whether Skit.ai can reach its next milestone before needing new capital.
  • Regulation: Changes from data protection rules under the Digital Personal Data Protection Act, sector regulators, consumer protection law and IT rules.

Industry Context: Where Skit.ai Fits

India's technology startup ecosystem is one of the largest in the world, supported by cheap data, a large base of smartphone users, digital public infrastructure and a deep engineering talent pool. Companies now build for education, software, mobility, logistics, agriculture, defence, media and more, selling both to Indian customers and abroad.

Durable technology companies usually combine a clear customer problem with repeatable distribution and disciplined unit economics. Growth funded only by spending tends to fade, while products that customers keep using and paying for build compounding advantages.

For readers new to this field, a useful habit is to separate announcements from evidence. A plan, a partnership or a funding headline describes intent, while a delivered product, a paying customer or an audited financial statement describes results. Comparing the two over time shows how reliably a company turns promises into outcomes.

Bull Case and Bear Case for Skit.ai

An investment thesis is a short, testable statement of why a company could become far more valuable, together with what evidence would prove it wrong. The points below are general to this sector and are not forecasts for Skit.ai.

Bull case

  • A large and growing base of digital users and businesses expands the addressable market.
  • Recurring revenue and strong retention can compound growth.
  • Selling into global markets widens the opportunity beyond India.

Bear case

  • Heavy competition can compress pricing and margins.
  • Dependence on external funding can force painful cost cuts.
  • Regulation or platform changes can disrupt a product quickly.

Lessons Founders and Investors Can Take from Skit.ai

Studying a company in the Voice AI space offers lessons that go beyond any single firm. The points below are general lessons for the sector and are not claims about Skit.ai.

  • Solving a clear, frequent customer problem matters more than adding features.
  • Retention and repeat usage are better health signals than sign-ups.
  • Disciplined spending extends runway and keeps options open when funding tightens.
  • Distribution, not just product quality, decides who wins in crowded markets.
  • Building trust through data protection and reliability is part of the product.

How to Evaluate Skit.ai as a Startup

  • Customer clarity: Can Skit.ai name its customer and the problem it solves in one sentence?
  • Evidence of demand: Look for repeat customers, signed contracts or measurable usage rather than announcements alone.
  • Economics: Check whether margins improve as volume grows.
  • Execution: Compare announced timelines with what has actually been delivered.
  • Funding runway: Estimate how long current capital lasts at the present spending rate.
  • Regulatory standing: Confirm required approvals are in place.
  • Customer concentration: Check whether a few customers account for most of the revenue.
  • Management depth: Look for experienced leaders beyond the founders and a stable core team.

The Takeaway

Skit.ai is part of India’s growing Voice AI ecosystem. The useful lesson from studying it is the discipline of asking structured questions about customers, economics, advantage and resilience. Companies that answer them well, repeatedly and under pressure are the ones that endure. Readers should treat any single report, ranking or funding headline as one input among many, and should re-check key facts against recent company announcements. Because public information on young companies is often limited, patience in verifying claims is part of good analysis. Public sources can also describe the same company in different ways, so it is worth checking dates, definitions and whether a figure refers to revenue, total income or transaction value, and whether it covers one entity or a wider group, before drawing conclusions. Small differences in rounding, currency conversion or reporting periods can also change how a figure reads. Comparing the same figure across several recent reports helps show whether it is stable or has changed over time. This article is educational and is not investment advice.

  • Clear customers and repeat demand matter more than announcements.
  • Regulation and capital needs shape how fast a startup in this sector can grow.
  • Track a few leading indicators over time rather than one headline metric.

Skit.ai FAQs: Frequently Asked Questions

What is Skit.ai?

Skit.ai (formerly Vernacular.ai, legal name Cyllid Technologies Private Limited) is a voice AI company founded in 2016, based in Bengaluru with a New York headquarters, focused on automating call-centre conversations, especially debt collection. It is profiled in the Startup Deep Dive series, which explains business model, funding, competitors and risks.

Who founded Skit.ai?

Skit.ai was founded by Sourabh Gupta, Akshay Deshraj, and the company reports a founding year of 2016.

How much funding has Skit.ai raised?

Reports differ: about $28 million to $53 million; TechCrunch said $30 million as of 2021. Funding figures are reported and may differ between sources, so readers should check the latest company announcements.

How does Skit.ai make money?

Skit.ai earns revenue from its Voice AI products and services sold to businesses, institutions, consumers, learners and public-sector buyers. The exact revenue mix is described in the business model section and is not fully disclosed publicly.

Who are the competitors of Skit.ai?

Reported rivals include Observe.ai, Yellow.ai, Gnani, Vodex. See the competitor comparison above for how they differ.

What are the main risks for Skit.ai?

Main risks include competition: low barriers to entry and well-funded rivals can compress pricing and slow growth, funding and capital needs, competition and regulation by data protection rules under the Digital Personal Data Protection Act, sector regulators, consumer protection law and IT rules. This is educational content, not investment advice.

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Source

Source: Publicly available data, published reports, industry research, and other credible sources.

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