API performance profiling
Distributed tracing to find exactly where time is spent in a request path.
API Optimisation
Systematic API performance analysis and optimisation: reducing response times, cutting unnecessary database queries, improving throughput under load, and lowering infrastructure costs through efficient API design.
APIs That Perform Under Real Load
1
Profiling & Analysis
- Request profiling with distributed tracing
- N+1 query detection and elimination
- Database slow query analysis
- Memory and CPU usage profiling
2
Optimisation Techniques
- Database query optimisation and indexing
- Response payload minimisation (field selection)
- Connection pooling configuration
- Pagination and cursor-based iteration
3
AI API Optimisation
- LLM prompt length reduction (token cost)
- Batch API call consolidation
- Streaming vs batch request strategy
- Model routing by query complexity
API Optimisation Services
From profiling to production improvements
N+1 query elimination
Detecting and eliminating N+1 database query patterns, the most common cause of slow APIs.
Database indexing
Index design and query plan analysis for slow database queries.
Response caching
Caching strategy for frequently-requested, rarely-changing API responses.
Pagination optimisation
Cursor-based pagination for endpoints that return large result sets.
LLM cost reduction
Prompt compression, model routing, and caching to reduce LLM API costs.
Load testing
Load testing endpoints under expected peak concurrency before launch.
Connection pooling
Connection pool tuning to prevent database connection exhaustion under load.
Optimisation Backed by Data
Profile Before Optimising
Every optimisation starts with profiling data, not a guess at what's slow.
N+1 Fixes First
N+1 query elimination is usually the highest-impact database fix available, and often the fastest to ship.
LLM Cost Optimisation
Prompt compression, model routing, and caching typically reduce LLM API costs significantly without a quality trade-off.
Verified Under Load
Every optimisation is load tested afterward to confirm the improvement holds under real concurrent traffic, not just a single-request benchmark.
Optimisation Backed by Data
Profile Before Optimising
Every optimisation starts with profiling data, not a guess at what's slow.
N+1 Fixes First
N+1 query elimination is usually the highest-impact database fix available, and often the fastest to ship.
LLM Cost Optimisation
Prompt compression, model routing, and caching typically reduce LLM API costs significantly without a quality trade-off.
Verified Under Load
Every optimisation is load tested afterward to confirm the improvement holds under real concurrent traffic, not just a single-request benchmark.
API Optimisation FAQs
N+1 database queries are the most common root cause of slow APIs. An N+1 query happens when the API fetches a list of N items, then makes one database query per item: resulting in N+1 total queries for what could be 1 or 2. This is almost always solvable with eager loading (JOIN queries), dataloader batching, or a query restructure. The fix typically reduces response times by 3–10x without any infrastructure changes.
We use distributed tracing (OpenTelemetry, Jaeger, Datadog APM) to profile individual request paths: seeing exactly how long each database query, external API call, and computation takes. This gives a data-driven view of where time is spent. We also use k6 or Locust for load testing: verifying behaviour under concurrent users, not just single-request latency.
Yes, LLM API cost optimisation is a speciality. The main levers: (1) prompt compression, removing unnecessary context while maintaining quality, typically saves 20–40% of input tokens; (2) model routing, using GPT-4o-mini or Claude Haiku for simple queries and reserving expensive models for complex ones; (3) caching, semantic caching for repeated queries; (4) batching, combining multiple small requests into single API calls. Combined, these typically reduce LLM costs 40–60%.
Trusted by Global Companies Building AI Products
We've helped startups and enterprises worldwide transform their AI ideas into production-ready MVPs in 2–3 weeks. From fintech platforms to AI assistants, our global MVP development services have launched 18+ AI products serving users across the US, Europe, and Asia.
Portfolio: AI Products Built for Global Startups
From content platforms and AI assistants to analytics dashboards and fintech solutions: see how we've transformed ideas into production-ready MVPs in 2-3 weeks across diverse industries. Each product here is one our team worked on.
UseArticle
AI-powered content creation and management platform that helps teams produce high-quality articles at scale.
AgentHi
Intelligent virtual assistant that streamlines customer support and automates routine business tasks.
StatsHub
Comprehensive analytics dashboard providing real-time insights and data visualization for businesses.
Harimaxx
Personal fitness companion with AI-driven workout plans and nutrition tracking for optimal health.
Vaga
Smart travel planning app that curates personalized itineraries and local experiences.
FoodScan
Nutrition analysis app that scans food items and provides detailed nutritional information instantly.
MyJobReach
Job matching platform connecting talented professionals with their dream opportunities.
TravelGram
Social platform for travelers to share experiences, discover destinations, and connect globally.
SuperStatz
Advanced sports statistics platform delivering in-depth analysis and performance metrics.
Cashbook
Simple expense tracking and budgeting app that helps users manage their finances effortlessly.
TypeFast
Typing speed improvement platform with gamified lessons and real-time performance tracking.
Easy Loan
Streamlined loan management system that simplifies borrowing and lending processes.
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