How Pax Historia Built and Scaled a Multi-Model AI Infrastructure with Infron

About Pax Historia

Pax Historia is a groundbreaking AI-powered alternate-history sandbox game incubated by Y Combinator (W26). Players can choose any country and any historical period, and use generative AI to rewrite the course of history. What if Rome never fell? What if the Soviet Union had survived? What if Genghis Khan had ruled for another generation?

The world of Pax goes far beyond historical re-enactment. Players can explore virtually any “what-if” scenario: an alien invasion of Earth, a college dropout building a tech empire, or even entirely fictional universes. Powered by advanced generative AI, players can freely create, edit, and share custom maps, characters, and historical backgrounds, experiencing almost any scenario they can imagine.

This unprecedented level of freedom and depth quickly attracted a highly engaged core player base. Within four months of the first alpha release, Pax organically built a passionate community with tens of thousands of daily active users and achieved exceptionally high retention compared to similar games. Players actively share their in-game scenarios on platforms like Reddit and Instagram, creating strong word-of-mouth growth.

The Scaling Challenge Behind the Magic

As the AI-driven gaming market continues to expand, Pax Historia stands at the forefront of a new wave of transformation in the gaming industry. However, this type of experience—built on large-scale AI models—also introduces unique technical challenges. To support real-time historical simulation, dynamic dialogue generation, and AI-driven strategic decision-making, Pax needs to call multiple types of AI models at the same time: from GPT-style models for dialogue, to Stable Diffusion for image generation, and to specialized models for strategic planning.

During this rapid growth phase, this multi-model dependency quickly turned into an operational nightmare for the Pax team, which consists of only two core founders. They had to maintain accounts across dozens of AI providers including OpenAI, Anthropic, Google, and Stability AI, handle a large number of fragmented invoices every week, and deal with frequent late-night incidents caused by API rate limits, quota exhaustion, and other stability issues.

The hidden infrastructure crisis

Cost pressure became even more severe. As daily active users grew to tens of thousands in a short period of time, each player session triggered dozens or even hundreds of AI model calls. With a pure pay-as-you-go setup across all providers, monthly AI compute costs grew exponentially, while the founding team simply did not have the time or resources to negotiate discounts with each provider individually.

Pax Historia urgently needed a unified AI infrastructure solution—one that could simplify vendor management, significantly reduce costs, and at the same time guarantee more than 99.9% service availability. For a real-time online game, any API outage directly translates into a catastrophic player experience.

Challenges

Before adopting Infron AI, Pax Historia faced three core challenges.

Fragmented Vendor Billing and Cost Management, Threatening Business Continuity

As a game deeply dependent on generative AI, Pax Historia needed to integrate with more than 30 different AI providers, covering large language models (OpenAI GPT, Anthropic Claude, Google Gemini), image generation models (Midjourney, Stable Diffusion, DALL·E), and various specialized models.

Each provider came with its own account system, billing model (token-based, per-API-call, subscription-based, etc.), and billing cycle. The two founders had to process dozens of invoices every week, and service outages caused by forgotten top-ups were not uncommon—directly impacting the experience of online players.

This fragmented financial setup was not only time-consuming, but also made unified cost analysis and budgeting almost impossible. The team often could not even answer a basic question like, “How much did we actually spend on AI last month?”, let alone optimize the overall cost structure.

Frequent API Stability Issues, Damaging Player Experience

Initially, Pax adopted an architecture that directly connected to each provider’s native API endpoints. This quickly led to serious stability issues:

• Quota limits: traffic spikes frequently hit provider quota ceilings, causing requests to be rejected

• Rate limiting: under high concurrency, rate limit errors were common, leading to severe in-game latency

• Provider-side outages: failures on any single provider directly broke game functionality, with no control on Pax’s side

Even more challenging, Pax’s small ops team did not have the time or capacity to communicate with every provider via email or ticket systems. Support requests often took hours or even days to receive a response.

To keep the service running, the team had to implement complex fallback logic inside their internal AI gateway—for example, switching from OpenAI to Anthropic when one failed, or retrying image generation with another provider on timeout. While this barely kept the system operational, it significantly increased system complexity and did not solve the root problem.

High and Uncontrollable Pay-as-You-Go Costs, with No Negotiation Leverage

Because Pax was connected to more than 30 AI providers and iterating extremely fast (constantly testing and switching models), the team had virtually no time to negotiate commercial agreements with any single vendor.

Relying entirely on standard pay-as-you-go pricing meant:

• No volume discounts: large customers often receive 20–40% discounts, but Pax had no capacity to negotiate

• Unpredictable costs: when user numbers surged, AI costs grew exponentially with no built-in safeguards

• No cost structure optimization: prices varied widely across providers, but the team lacked the data and tools to make informed optimization decisions

As daily active users reached tens of thousands, AI compute quickly became the company’s second largest expense (after headcount), severely squeezing the budget for product development and marketing. For an early-stage startup, this cost structure was simply not sustainable.

The Solution

To address these challenges, Pax Historia introduced Infron AI as its unified AI infrastructure layer in Q4 2025. Infron AI is not just an API gateway, but a full enterprise-grade AI model management platform.

Unified API Access and a Simpler Architecture

The Pax team upgraded their internal AI gateway architecture:

• From directly integrating with 30+ provider endpoints → to integrating only with Infron AI

• All model calls now use a unified OpenAI-compatible SDK format, eliminating provider-specific integration logic

• Switching between providers is as simple as changing the model name (e.g., gpt-4, claude-3-opus)

This change significantly simplified the codebase and drastically reduced the effort required to onboard new models.

Centralized Billing and a 90% Improvement in Financial Operations Efficiency

After adopting Infron AI, Pax’s financial operations were fundamentally transformed:

• From processing 30+ fragmented invoices every week → to receiving a single monthly invoice from Infron

• Supports both invoice-based billing and automatic credit card top-ups, completely eliminating outages caused by forgotten recharges

• A unified dashboard provides real-time visibility into:

  • Usage and cost breakdown by model

  • Cost trends over time

  • Cost attribution by product feature or module

Overall financial operations efficiency improved by 90%, finally freeing the two founders from endless billing work so they could focus on product innovation.

Intelligent Routing and Automatic Fallback, Raising Reliability to 99.9%

One of Infron AI’s core strengths is its provider routing and model fallback system:

• A global, real-time health monitoring system tracks API availability, latency, and error rates across 60+ providers, 24/7

• An intelligent routing engine automatically sends requests to the optimal provider based on price, throughput, latency, and parameter fit

• Automatic failover transparently switches traffic to backup providers when any provider is degraded or rate-limited

As a result:

• Average API error rates dropped from 8–10% to below 0.5%

• Overall service availability reached 99.9% SLA

• The ops team no longer needs to deal with emergency API incidents in the middle of the night

Enterprise Discounts and Intelligent Optimization, Cutting Costs by 60%

Infron AI helped Pax reduce AI costs on two levels.

1. Enterprise volume discounts

As an aggregation platform, Infron maintains enterprise partnerships with major AI providers. Through Infron, Pax can access discounts of up to 35% that would normally only be available to large enterprise customers.

2. Intelligent cost optimization

• Automatically selects the most cost-effective option among functionally equivalent models (e.g., dynamically switching between Claude and GPT)

• Automatically downshifts to cheaper models for tasks that do not require maximum accuracy

• Provides detailed cost analysis reports to help the team identify further optimization opportunities

Combined, these measures reduced Pax’s total AI compute costs by 60%, saving tens of thousands of dollars per month, which were reinvested into game content development and community operations.

24/7 Dedicated Support for Critical Moments

In addition to the product itself, Infron AI provides enterprise-grade customer success support:

• A dedicated Slack group for direct access to Infron’s engineering team

• White-glove support during major releases and marketing campaigns, with real-time monitoring

• Priority support SLAs: any issue responded to within 1 hour, critical issues addressed within 30 minutes

For a small team, this level of support is invaluable and enables Pax to iterate quickly without worrying about infrastructure stability.

Results

Six months after adopting Infron AI, Pax Historia achieved significant improvements in both operational efficiency and cost control:

More importantly, these improvements freed up the team’s time and focus:

The founding team no longer spends around 30% of their time on vendor management and can focus on product strategy and community growth. Engineering iteration speed increased by 200%, enabling faster experimentation with new models and game mechanics. Operational pressure dropped significantly, and late-night emergency calls have nearly disappeared.

These efficiency gains translated directly into business results. In the six months after adopting Infron AI, Pax Historia’s DAU grew by 300% while maintaining industry-leading retention. Organic sharing on social platforms increased by 250%, making Pax one of the most talked-about consumer AI products in the YC W26 batch.

Customer Testimonial

“Infron AI completely changed how we manage our AI infrastructure. As a fast-growing startup, we were drowning in chaos—managing 30+ AI providers, processing dozens of invoices every week, waking up at night to deal with API failures, and watching costs spiral out of control. Infron didn’t just simplify everything into one unified interface and one monthly bill. More importantly, with intelligent routing and enterprise discounts, our AI costs dropped by 60% while our service reliability improved to 99.9%. Now we can invest our time and budget in what really matters: building a better experience for players. If your product depends heavily on AI models, Infron AI is an infrastructure layer you simply can’t live without.”

— Ryan Zhang
Co-Founder, Pax Historia | YC W26

About Infron AI

Infron AI is a unified AI model routing platform built for high-growth companies. It provides:

• A single API to access 300+ mainstream AI models

• Enterprise-grade discounts saving up to 35% on AI API costs

• 99.9% SLA with intelligent routing and automatic failover

• Unified billing with enterprise invoice support

• 24/7 dedicated technical support for mission-critical workloads

Infron AI serves dozens of YC-backed companies including Pax Historia and has processed more than 6 trillion tokens across its platform.

Ready to optimize your AI infrastructure? Contact the Infron AI team to get a tailored solution.