CHAI AI

Business Profile

Core Value Proposition

CHAI AI provides a platform to build, deploy, and scale social AI-powered chat experiences and user-generated ChatAIs (UGAI) at large scale.

Target Customer

Consumers who want to create and interact with customizable ChatAIs; developers and researchers building AI platforms; quant traders and finance teams exploring AI tooling.

Key Differentiator

In-house, end-to-end social AI platform with Model Mesh orchestration; vast GPU-backed compute (up to 5000 GPUs; >1.4 exaflops); thousands of production LLMs (51K unique LLMs); advanced model blending (Best-of-8, 10x24B); RLHF/DPO-based improvements driven by user signals; first consumer AI platform enabling user-generated ChatAIs ahead of major competitors.

Implementation Timeline

Milestones and deployments include: Nov 2022 – CHAI Launches on App Store (consumer ChatAIs); Feb 2023 – First in-house 6B LLM; Mar 2023 – Best-of-4 reward model; May 2023 – 13B architecture; Jun 2023 – PPO model; Oct 2023 – Efficient inference with custom GPU orchestration; Nov 2023 – Increased GPU reservations (1000 A100); Dec 2023 – BO8 reward model; Mar 2024 – DPO model deployed; Aug 2024 – Upgraded all blends to DPO; Sep 2024 – 13B reward model; Oct 2024 – 10x 24B models deployed; Jan 2025 – Model Mesh orchestrator deployed; Mar 2025 – GRPO deployed.

Pain Points

1Need to deliver engaging, social, and factually correct AI at scale to millions of users
2Requirement to manage and serve hundreds to thousands of LLMs with low latency and high reliability
3Need for advanced model improvement loops (RLHF, DPO, Rejection Sampling) driven by user signals and efficient infrastructure

Key Features

1Platform to build and deploy social AI/ChatAIs with iOS, Android, and web access
2Model blending and ensemble approaches (e.g., 10x24B models) to boost engagement
3Model Mesh: in-house cluster orchestration enabling multi-cluster, multi-GPU-type serving at high throughput (>10K requests/sec)
4Custom CUDA kernels and GPU orchestration for efficient inference (beyond off-the-shelf solutions like vLLM)
5Large-scale LLM management (5000 GPUs, 1.2T tokens/day, 51K unique LLMs) with scalable infrastructure

Target Customer Industries

Decision Makers

1CEO
2Founder
3Engineer
4Researcher

Client Results

1Users: grew from 1 million in early 2022 to over 10 million by 2025
2Active users: Daily Active Users (DAU) grew from 800K to 2M; average session length increased from ~60 to ~90 minutes
3Engagement improvements: 60% higher engagement with 10x24B blended models vs GPT-4o; 20% engagement boost from DPO; 15% engagement improvement from GRPO
4Scale metrics: over 1.2 trillion tokens served per day; >10K requests per second across GPUs and model architectures
5Infrastructure: 5000 GPUs in cluster; >1.4 exaflops of compute performance; 51K unique LLMs served

Competitive Advantages

1Proprietary in-house GPU cluster and custom CUDA kernels enabling higher performance than generic solutions
2Model Mesh: scalable, multi-GPU-type serving to support hundreds of LLMs with high throughput
3Model blending and advanced RLHF/DPO techniques yielding significant engagement improvements
4Early mover advantage as a consumer AI platform enabling user-generated ChatAIs
5Large, active user base with long average session times, enabling rapid iteration and monetization opportunities

Key Benefits

1Scalable, high-engagement social AI experiences

2Extensive model experimentation with blending and RLHF/DPO

3Robust, high-throughput inference infrastructure (thousands of GPUs, multi-cluster orchestration)

4Early consumer AI platform with user-generated AI capabilities

Additional Product Information

Product Description

CHAI AI is a leading platform for building, researching, and deploying social AI and large language models, including a consumer-facing app store experience, in-house LLMs, model blending, and scalable inference via a dedicated GPU cluster and orchestration layer.

Target Market

Consumers and developers building social AI experiences; researchers and engineers designing scalable AI platforms; finance/quant teams exploring AI-driven tooling.

Unique Value Proposition

A scalable, social-focused AI platform with end-to-end in-house research, thousands of production LLMs, advanced model blending, and bespoke GPU orchestration to deliver engaging AI experiences at scale.

Technical Requirements

Requires a large GPU compute infrastructure (5,000 GPUs noted); custom CUDA kernels and in-house inference/ Orchestration (Model Mesh); large-scale multi-LLM serving; production-ready on iOS, Android, and web.

Pricing Model

Not specified

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