Sybill

Sybill provides AI software that integrates emotional intelligence into video calls, acting as an advanced partner for sales teams. Employing computer vision and artificial intelligence, the platform analyzes conversations, delivering real-time and post-call insights. This technology enhances salesperson understanding of prospect behavior and sentiment, offering data-driven intelligence to optimize sales interactions.

Founded in 2020 by Gorish Aggarwal, Mehak Aggarwal, Nishit Asnani, and Soumyarka Mondal, the company arose from an insight into the need for deeper human interaction analysis in virtual B2B sales. The founders recognized AI's potential to interpret conversational nuances, enabling professionals to build stronger rapport and improve communication.

B2B sales representatives and their organizations utilize Sybill's product to refine virtual selling. The company's vision is to empower these professionals with profound prospect understanding, fostering impactful connections and accelerating deal closures. Sybill continuously evolves its AI capabilities, providing sophisticated support throughout the sales journey.

High-Level Overview

Sybill is a portfolio company building an AI-first sales assistant that automates administrative tasks for B2B sales teams, enabling reps to spend less time on CRM updates and more on closing deals.[1][2][3] It serves sales organizations by analyzing calls, emails, and messages across the entire deal cycle, providing accurate deal summaries, auto-generated follow-ups, buyer insights, and risk alerts—saving reps over 2-5 hours weekly on manual work.[1][3][4] The platform solves the problem of fragmented conversational intelligence tools by using proprietary in-house models and retrieval-augmented generation (RAG) for holistic, context-aware analysis, outperforming single-call focused competitors.[2][3][4] Sybill has demonstrated strong growth momentum: 15X revenue increase over 18 months, tripling headcount, serving over 500 customers, and scaling ARR from $100K to $1M in 9 months via product-led growth with 60-70% of new revenue from referrals.[1][2][4]

Origin Story

Sybill was founded in 2020 by CEO Gorish Aggarwal, a former Stanford lecturer, alongside co-founders Nishit Asnani (UC San Diego), Soumyarka Mondal (Stanford), and Mehak Aggarwal (Harvard)—all AI experts with machine learning research experience since 2013.[1][2][3] The idea emerged when Gorish struggled to manage Zoom classes remotely, reading non-verbal cues, taking notes, and assessing feedback; he recognized parallels in B2B sales where every buyer interaction demands context.[1][2][3] After two years of research, including interviews with 600 sales reps, the team built in-house AI models, launching the comprehensive sales assistant platform in 2022—predating the ChatGPT hype.[1][2] Early traction was product-led, with rapid adoption driven by sales rep referrals, leading to an oversubscribed $11M Series A in 2024 (total raised: $14.5M) led by Greycroft, plus Neotribe Ventures, Powerhouse Ventures, Uncorrelated Ventures, and angels.[1][2][3][4]

Core Differentiators

• Holistic Deal-Level Analysis: Unlike call-only tools (e.g., Gong, Chorus.ai, Otter), Sybill uses proprietary RAG pipelines and in-house models to process calls, emails, and messages across the full deal cycle, detecting patterns like buyer hesitation or competitors for more accurate summaries and insights.[2][3][4]
• Sales-Specific Accuracy: Custom AI grasps sales nuances (e.g., decision-makers, critical events) without explicit mentions, minimizing hallucinations and building trust—reps save 2-5+ hours weekly on admin.[1][3][4]
• Product-Led Growth and Rep-Friendly Design: 60-70% new revenue from referrals; adapts to diverse sales processes/deal sizes without replacing reps, focusing on amplifying human strengths.[1][2][4]
• In-House Tech Edge: Founders' deep ML research enables superior models over LLM wrappers, with comprehensive outputs like auto-emails and risk alerts.[1][2][3]

Role in the Broader Tech Landscape

Sybill rides the generative AI wave in sales enablement, addressing a crowded market of transcription and grunt-work tools that fail to boost seller effectiveness amid exploding LLM wrappers.[1][2][4] Timing is ideal post-ChatGPT, as B2B sales demand trusted, accurate AI for deal acceleration—Sybill's pre-AI-hype origins and research depth position it ahead.[1][2] Market forces like remote selling persistence, admin overload (e.g., CRM data entry, RFP grunt work), and need for visibility favor it, influencing the ecosystem by redefining sales reps as "top performers" via autonomous task completion and deeper insights.[1][3][4] It sets a benchmark for context-aware, sales-native AI, potentially reshaping how teams operate without displacing humans.[3]

Quick Take & Future Outlook

Sybill's trajectory points to expanded AI capabilities, automating more admin tasks and delivering advanced buyer insights to transform sales workflows.[1][2] Trends like frontier AI integration and sales process efficiency will propel it, especially as trust in accurate outputs becomes table stakes in a hallucination-prone market.[4] Its influence may evolve from niche disruptor to category leader, empowering B2B teams to close deals faster—building on its referral-fueled momentum to capture a slice of the booming sales AI space.[1][2][4] This positions Sybill as a foundational player in AI-augmented selling, echoing its origins in solving real rep pain.