How Agnes AI Reached 3M Users While Cutting AI Costs by 60% with Infron

About Agnes AI

Agnes AI is an AI-native social collaboration platform built to redefine how people work and create with AI. Unlike traditional productivity tools or simple ChatGPT alternatives, Agnes AI combines real-time AI assistance with social collaboration, creating a shared creative environment where teams can work together seamlessly.

At the heart of Agnes AI is CoVibe, a group collaboration space where users can invite friends and teammates to co-create with AI in real time. Inside a CoVibe group, any member can @Agnes AI to generate presentations, create images and videos, apply creative filters, research complex topics, or get instant answers. All results are synchronized in real time, enabling faster ideation, smoother collaboration, and higher creative output.

Market Traction and Growth Challenges

Agnes AI primarily serves young users in emerging markets across Asia, Africa, and Latin America. Thanks to its unique social + AI collaboration experience, the product achieved explosive growth. Since its official launch in September 2024, Agnes AI surpassed 3 million users in just two months, with an 8-week retention rate of 30%, significantly above industry benchmarks.

However, rapid growth also introduced serious technical challenges.

As the product evolved, Agnes AI needed to support an increasingly diverse set of AI capabilities — from text generation and image creation to video editing and voice synthesis. This required integrating dozens of AI model providers, each with different APIs, billing systems, performance characteristics, and reliability profiles.

At this critical scaling stage, the team found themselves stuck in what they described as a “vendor management nightmare”:

• Engineers had to maintain integrations with dozens of providers.

• The ops team processed tens of invoices and top-up alerts every week.

• Stability alerts in the middle of the night became routine.

The growing complexity of the AI infrastructure was draining engineering focus and becoming a major bottleneck for product iteration.

Even worse, cost pressure was rising fast. As a high-growth startup, Agnes AI relied entirely on pay-as-you-go pricing across all AI providers. With fragmented usage and no bargaining power, compute costs remained high and unpredictable, putting increasing pressure on margins.

Challenges

Before adopting Infron, Agnes AI faced three core problems.

1. Fragmented Billing and Vendor Management Chaos

As product features expanded, Agnes AI integrated with 20+ AI providers including OpenAI, Anthropic, Replicate, ElevenLabs, Stable Diffusion, and more. Each had:

• Separate accounts and API keys

• Different billing systems and top-up workflows

• Different pricing units (tokens, requests, seconds, images, etc.)

The ops and finance teams had to:

• Manage dozens of credentials and API keys

• Process 20+ invoices and top-up reminders every week

• Deal with service outages caused by forgotten top-ups

• Reconcile multi-currency, multi-pricing-model invoices during financial close

This fragmented setup was not only inefficient, but also risky. Human errors frequently caused service interruptions that directly impacted users.

2. Frequent Stability Issues and Slow Incident Response

Agnes AI was directly calling each provider’s native endpoint, which led to recurring issues:

• Quota limits during traffic spikes

• Rate limiting during peak usage

• Regional instability and high latency in certain markets

• Sudden model deprecations without advance notice

When incidents happened, the team had to:

1. Identify which provider caused the issue

2. Contact the provider via email or ticket system (24–48h response time)

3. Manually configure fallback logic in their internal gateway

4. Handle urgent incidents late at night

With so many vendors and fragmented communication channels, the ops team was constantly firefighting and had no systematic reliability strategy.

3. High Pay-as-You-Go Costs and No Negotiation Power

As a fast-growing startup, Agnes AI used standard pay-as-you-go pricing across all providers:

• No access to enterprise volume discounts

• Frequent model switching made long-term contracts impractical

• No dedicated procurement team to negotiate prices

• No easy way to compare cost-performance across providers in real time

As a result, AI compute became the second largest cost after headcount, significantly impacting profitability and company valuation.

The Solution: Infron as the Unified AI Infrastructure Layer

To fundamentally solve these challenges around vendor management, system reliability, and cost control, Agnes AI introduced Infron as its unified AI infrastructure platform.

Instead of directly integrating and operating more than 20 different AI providers, Agnes AI re-architected its internal AI gateway to route all model calls through a single, standardized Infron API.

This immediately simplified both engineering and operational complexity:

• From directly integrating 20+ providers → to integrating only Infron

• All model calls now go through Infron’s standardized API

• Billing is centralized via invoice and automatic credit card top-ups

Results:

• Finance operations efficiency improved by 90%

• Weekly billing work dropped from 8 hours to less than 1 hour

Solving Vendor Chaos: Unified Access and Centralized Operations

To address the fragmented vendor management and billing chaos, Agnes AI consolidated all AI provider access through Infron.

Instead of managing dozens of accounts, API keys, and top-up workflows across different platforms, the team now operates everything through a single unified interface, dramatically reducing operational overhead and the risk of human error.

This change alone eliminated a large class of service interruptions caused by forgotten top-ups or account issues and significantly simplified financial reconciliation.

Solving Reliability Issues: Intelligent Routing and Automatic Fallback

To address frequent outages, rate limits, and regional instability across different providers, Agnes AI adopted Infron’s intelligent routing and automatic model fallback mechanisms.

With Infron:

• Each request is dynamically routed to the best available provider in real time based on price, latency, throughput, availability, and parameter fit

• Degraded or rate-limited providers are automatically avoided

• When a primary model becomes unavailable, traffic is seamlessly switched to backup models with zero user-visible downtime

As a result, Agnes AI eliminated single points of failure across providers and significantly improved overall system stability and resilience.

Solving Cost Pressure: Real-Time Cost Optimization and Bulk Discounts

To address rising and unpredictable pay-as-you-go costs, Agnes AI started using Infron’s real-time price-performance optimization and centralized purchasing power.

Instead of passively paying standard on-demand prices across dozens of vendors, Agnes AI can now:

• Compare price-performance across providers in real time

• Automatically route traffic to the most cost-effective options

• Benefit from bulk discounts negotiated by Infron and passed on to customers

This directly led to a 60% reduction in total AI compute costs, turning AI infrastructure from a growing financial burden into a predictable and scalable cost structure.

24/7 Enterprise-Grade Support

Beyond the product itself, Infron also provides enterprise-grade operational support:

• A dedicated Slack support group with real-time responses

• Special support coverage during major launches and campaigns

• Proactive monitoring and early incident prevention

This ensures that Agnes AI’s team no longer needs to personally handle urgent provider incidents around the clock and can focus on product development instead of infrastructure firefighting.

Results

After adopting Infron AI, Agnes AI achieved dramatic improvements in both efficiency and cost control:

• Development iteration speed: +300%

• Average AI API error rate: -90%

• Total AI compute cost: -60%

• Vendor management workload: -95%

• Mean Time To Recovery (MTTR): from 2 hours to 5 minutes

Business Impact

With Infron AI in place, the team no longer needs to wake up at night to deal with provider outages, allowing engineers to shift their focus from infrastructure maintenance to product innovation. At the same time, cost predictability has improved significantly, enabling a healthier and more sustainable scaling model. As a result, the overall user experience has become much more stable, with AI interactions in CoVibe now achieving near-100% success rates.

Customer Testimonial

“Infron truly helped us achieve our goal of focusing on product, not infrastructure. Our engineers used to spend around 30% of their time dealing with AI vendor issues. Now it’s less than 3%. More importantly, we reduced costs by 60%, which is a massive competitive advantage for a fast-growing company like us. Infron is not just a technology provider, they feel like a true technical partner.”

— Bruce Yang
Co-Founder & CEO, Agnes AI

About Infron

Infron is a next-generation AI infrastructure platform that gives enterprises a single, unified way to access AI models, with built-in intelligent routing, cost optimization, and reliability guarantees. With one API, companies can connect to more than 300 AI models worldwide, reducing AI costs, simplifying vendor management, and improving system reliability.

Ready to simplify your AI infrastructure? Contact the Infron team