We solve the engineering problems that keep good products from scaling.
ProxyPattern is a boutique software architecture and AI engineering firm. We design simple systems, eliminate moving parts, and scale backend infrastructure for ambitious software teams.
Supported under high load
Through semantic caching
Through container autoscaling
Through schema partitioning
Scaling a live Conversational AI pipeline.
A growing customer support platform was spending thousands of dollars on direct GPT-4 API calls. Sluggish response times (latency) were causing customer churn, and database lockups blocked operations.
Instead of rewriting the application, we decoupled the architecture. We implemented semantic Redis caching to serve repeated queries instantly, offloaded audit persistence to Sidekiq, and optimized the streaming connections.
System Architecture Flow
How We Approach Systems
We don't guess. We follow a strict, metric-driven engineering process to understand, audit, and clean up software codebases.
Core Engineering Principles
We have a recognizable engineering philosophy. We build software that compounds in value over time.
Complexity is debt with interest.
Every line of code, dependency, or server configuration is a liability. We design to remove moving parts. Simple code is cheaper to write, easier to debug, and faster to scale.
Determinism before AI.
Large Language Models are probabilistic engines. Before adding an AI model to your stack, ask if a database query, state machine, or simple regex can solve it. Keep your system deterministic where possible.
Prefer boring technology.
We build systems using stable, mature stacks (Rails, Next.js, PostgreSQL, Redis). We focus on maximizing their native capabilities rather than constantly introducing new libraries.
Simplicity scales.
Scaling isn't about rewriting your app in Rust; it's about database indexing, caching strategies, efficient queue processing, and removing N+1 queries. Monoliths scale incredibly well when built properly.
Architecture is leverage.
Good system design compounds. When your database schema matches your business domain, feature velocity stays fast. When it doesn't, engineering speed grinds to a halt.
What We Fix
Our consulting solutions focus entirely on systemic bottlenecks and data architecture.
Fixing the database bottlenecks that stop products from growing.
// PostgreSQL & Monolith Scalability
Most database performance issues aren't caused by PostgreSQL limits—they are caused by database schemas and transaction hold times that stopped matching the product.
Explore Database Audits →Building AI features that customers actually trust in production.
// Low-Latency LLM Orchestration
Most AI failures aren't model reasoning failures—they are orchestration, prompting, streaming, and database sync failures that cause lag and hallucinations.
Explore AI Engineering →We teach what we build.
We share our engineering approaches, open-source libraries, and complexity guides. You can audit how we solve problems before scheduling a call.
The Playbook
Read our exact frameworks: how we programmatically evaluate AI systems, find PostgreSQL queries holding locks, and decide when NOT to use AI.
Open the PlaybookOpen Source
Audit our public codebases. We build public utilities like GemGuard to track lockfile packages and validate dependencies in CI.
View GitHub Code