Introducing hallucination correction. We have reduced hallucination by 70%. Giga's hallucination rate is at ~1%. Better than the best frontier models.
Deploy AI your customers can trust.
lots of great startup lessons from @varunvummadi leading Giga. quickly becoming a generational company that is taking down some formidable competitors. Great having him at Startup School in India earlier this year!
Varun Vummadi (@varunvummadi) is the co-founder of @GigaAI, which builds AI agents for customer support for some of the biggest companies in the world, including DoorDash, one of the largest crypto exchanges in the US, and a top-three global telecom provider.
At Startup School India, Varun sat down with YC's @agupta to talk about why he turned down a high-paying quant job to start a company, the multiple pivots it took to find the right problem, and how their small team of eight beat a 400-person competitor to land a contract with DoorDash.
01:33 — Early Days & Origin Story
03:37 — The YC Interview Disaster
06:28 — Pivoting Away From EdTech
07:25 — Finding the Real Idea
08:39 — Beating a Well-Funded Competitor
10:00 — Winning DoorDash With 8 People
11:09 — What GigaML Looks Like Now
12:40 — Advice for College Students
15:51 — Why Charge Early?
17:33 — The Next Big Bet
18:43 — Running the Company on AI
20:19 — How They Hire Engineers
22:04 — Product Over Sales
23:37 — Burn the Boats
Introducing hallucination correction. We have reduced hallucination by 70%. Giga's hallucination rate is at ~1%. Better than the best frontier models.
Deploy AI your customers can trust.
“Most people fine-tune models for two reasons: cost and speed.”
@varunvummadi CEO of @GigaAI:
“Fine-tuning reduces cost, increases speed, and improves throughput.”
“Some industries like healthcare and finance also prefer it because they don’t want to rely on closed-source models.”
“But when we looked at the data, two use cases dominated: support and coding.”
“So we decided to focus on support and double down there.”
🧵 Understanding this concept deeply is fundamental to what makes @GigaAI so special. It's one of the biggest reasons I joined (beyond getting the chance to work with @eshamanideep and @varunvummadi).
Come see @eshamanideep (our CTO) talk about @GigaAI at @ycombinator HQ on December 10th! I'll be there as well.
We're hiring the most ambitious engineers across the stack to build the future of AI support agents for the largest B2C companies in the world.
Link below
If you are wondering how Giga gets enterprise customers live in weeks, not months.
Check out our founders’ chat with @harjtaggar where they talk about how we turns plain English into code to deliver speed and scale at the enterprise level.
Something that stunned me about @gigaai is they've moved away from the FDE playbook that's become the default for fast growing AI startups. Instead they've built AI to covert plain English from the customer into Python code to make the product work for their use cases i.e. an AI FDE. It's a huge technical feat and is how they can onboard enterprises in weeks vs months.
Check out @varunvummadi and @eshamanideep’s conversation with @harjtaggar, where they share how Giga’s unique approach enables unmatched speed, scale, and performance for enterprise customers like @DoorDash:
Giga (@gigaai) is building the next generation of customer support — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.
The team recently raised $61M to power emotionally intelligent, human-quality conversations at enterprise speed and scale.
In this interview with YC's @harjtaggar, co-founders @varunvummadi and @eshamanideep share how they’re reimagining enterprise support from the ground up, what it takes to build AI for high-compliance industries, and why emotionally intelligent agents are the future of customer experience.
02:25 – What Giga Does and Who It Serves
05:10 – Building Emotionally Intelligent AI Agents
08:15 – Real-Time Responses at Enterprise Scale
11:45 – Designing for Compliance and Security
15:00 – Human-Quality Conversations at Machine Speed
18:20 – Lessons from Early Customer Deployments
22:10 – Powering the Next Generation of Support
26:45 – What It Takes to Build for the Enterprise
30:15 – The Future of Customer Experience
33:40 – Advice for Founders Building in AI
Giga (@gigaai) is building the next generation of customer support — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises.
The team recently raised $61M to power emotionally intelligent, human-quality conversations at enterprise speed and scale.
In this interview with YC's @harjtaggar, co-founders @varunvummadi and @eshamanideep share how they’re reimagining enterprise support from the ground up, what it takes to build AI for high-compliance industries, and why emotionally intelligent agents are the future of customer experience.
02:25 – What Giga Does and Who It Serves
05:10 – Building Emotionally Intelligent AI Agents
08:15 – Real-Time Responses at Enterprise Scale
11:45 – Designing for Compliance and Security
15:00 – Human-Quality Conversations at Machine Speed
18:20 – Lessons from Early Customer Deployments
22:10 – Powering the Next Generation of Support
26:45 – What It Takes to Build for the Enterprise
30:15 – The Future of Customer Experience
33:40 – Advice for Founders Building in AI
We have raised $61M, but that’s not what excites me.
Our original idea was fine tuning LLMs for enterprises. Although we topped some benchmarks, the business was not viable.
We have raised a $61M Series A to automate customer operations.
The world’s leading companies like DoorDash trust Giga to supercharge customer experience with AI.
@andyfang Next up: we’re pushing toward 98% resolution and expanding how AI agents transform enterprise-scale customer support.
Check out the full story: https://t.co/PxjhCrI80C
Excited to share our partnership with DoorDash.
Together we went from kickoff to real impact — in weeks, not quarters.
Highlights:
- Time to value: weeks, not quarters
- Quality at scale: 90%+ DWR in production
- Built for scale: 10B+ lifetime orders, 500K+ merchants, 8M+ Dashers, and hundreds of thousands of daily assistance requests
As @AndyFang, Co-founder of DoorDash, put it best:
“At DoorDash, we operate at massive scale across services, platforms, and languages. Giga leveraged usage data to deliver measurable improvements — fewer escalations, faster resolution paths, and more efficient workflows as we grow globally.”