Giga
Giga builds AI agents for enterprise customer support and operations, providing emotionally intelligent, real-time voice and chat agents that handle complex workflows with human-like memory and context.
At a Glance
- Large enterprises and Fortune 100 companies
- E-commerce platforms
- Financial services and banking
- Healthcare providers
- +4 more
AI Tools by Giga
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Giga AI
Codebase Context Generator for AI
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Latest News
Giga Raises $61M in Series A Funding Led by Redpoint Ventures
Giga Launches Browser Agent for End-to-End Enterprise Automation
Giga Issues Statement on Extortion Attempt: 'Setting the Record Straight'
Giga Introduces Smart Insights for AI-Driven Performance Optimization
Products & Services
A low-code platform for building, governing, and scaling bespoke AI agents. Includes Agent Builder for voice/chat/multi-modal design, Atlas (built-in AI assistant), policy writing tools, simulations for testing, data source integration, and a structured deployment pipeline. Enables deployment in under two weeks.
Analytics and performance optimization tool that analyzes voice and text tickets to detect patterns, identify root causes, and generate actionable recommendations. Provides AI-generated policy updates, projected impact analysis, and continuous feedback loop for KPI improvement.
Enterprise-grade voice AI agents with ultra-low latency (<0.5 seconds), emotion-aware capabilities, and support for 90+ languages. Features personalized voices, dynamic interrupts, accent adaptation, multi-turn reasoning, and intent/context awareness for human-like conversations.
AI agent that operates directly in the browser without requiring APIs. Capable of logging into systems, navigating web applications, filling forms, and completing end-to-end tasks autonomously. Supports legacy systems, third-party software, and modern SaaS applications.
Market Position
Giga positions itself as building foundational AI infrastructure for enterprise customer voice and operations, differentiating through: (1) Ultra-low latency voice response (<0.5s) with emotion awareness, (2) Rapid deployment in under 2 weeks vs. months for competitors, (3) >90% resolution accuracy in production with self-improving capabilities, (4) Multi-modal real-time orchestration handling complex multi-party scenarios, (5) Enterprise-grade security with on-premise deployment options for regulated industries, (6) Comprehensive platform combining Agent Canvas, Insights, Voice, and Browser automation, (7) Support for 90+ languages with cultural fluency. Competes against traditional contact center software, voice AI providers like PolyAI and Assembled, and conversational AI platforms, but claims superior performance through emotionally intelligent agents and unified infrastructure.
Leadership
Founders
Varun Vummadi
Co-Founder & CEO. Bachelor of Technology in Electrical Engineering from IIT Kharagpur. Forbes 30 Under 30 alumnus. Rejected Stanford PhD admission and a $525,000 HFT (High-Frequency Trading) job offer to build Giga. Previously worked on AI research at Stanford University and taught at AlgoZenith. Also involved with the Entrepreneurship Cell at IIT Kharagpur.
Esha Manideep Dinne
Co-Founder & CTO. Bachelor's degree in Computer Science from IIT Kharagpur (GPA 9.79, Institute Rank 3). Forbes 30 Under 30 alumna. Rejected a $150,000 systems engineer role at a prominent Indian HFT firm. Previously interned at Quadeye (quant trading firm). Served as President of the Maths Club at IIT Kharagpur and was a member of NSS IIT Kharagpur.
Executive Team
Varun Vummadi
Co-Founder & CEO
IIT Kharagpur electrical engineering graduate, Forbes 30 Under 30, former Stanford researcher
Esha Manideep Dinne
Co-Founder & CTO
IIT Kharagpur computer science graduate (GPA 9.79, Rank 3), Forbes 30 Under 30, former Quadeye intern
Board of Directors
Founding Story
Giga was founded in 2023 by IIT Kharagpur alumni Varun Vummadi and Esha Manideep Dinne in their college dorm. Both founders rejected lucrative job offers—Varun turned down a $525,000 HFT position and Stanford PhD admission, while Esha declined a $150,000 systems engineering role—to pursue their vision of building AI that could transform enterprise operations. Initially focused on fine-tuning large language models (LLMs) for on-premise enterprise deployment, they pivoted to customer support automation after identifying a massive opportunity to solve broken customer experiences with emotionally intelligent AI agents.
Business Model
Revenue Model
Enterprise SaaS with custom pricing based on AI agent complexity, number of channels, deployment type (cloud vs. on-premise), and expected support volume. Revenue generated through API usage, enterprise subscriptions, and professional services including setup, implementation, training, and premium support.
Pricing Tiers
Bespoke pricing based on factors including agent complexity, channel count, deployment type, support volume, setup fees, implementation costs, team training, and premium support. On-premise deployment more expensive than cloud options.
Target Markets
- Large enterprises and Fortune 100 companies
- E-commerce platforms
- Financial services and banking
- Healthcare providers
- Telecommunications companies
- High-compliance industries requiring on-premise deployment
- Customer support automation for high-volume enterprise contact centers
- Multi-party coordination (e.g., managing Dashers and consumers simultaneously)
- Geofence mismatch and delivery verification
- Compliance and fraud detection in financial services
- Identity verification and account onboarding
- Loan application processing and credit card management
- DoorDash
- Multiple financial services clients
- Companies in healthcare sector