AI API Development & Integration Services
Custom AI API development including LLM wrappers, multi-model gateways, authentication, rate limiting, and SDK generation. Production-ready AI APIs for your applications.
Service Overview
AI APIs are the connective tissue that lets your applications leverage AI models reliably, securely, and at scale. At aimodels.in, we design and build custom AI APIs that expose model capabilities to your products with proper authentication, rate limiting, monitoring, and documentation. Our services cover everything from LLM API wrappers and proxies that add caching and fallback logic, to multi-model gateways that route requests across providers for cost and latency optimization. We build APIs that handle the full lifecycle of AI interactions including streaming responses, async batch processing, and webhook callbacks for long-running tasks. Whether you need an internal API for your team or a public API for customers, we architect solutions with OpenAPI specifications, auto-generated SDKs, and developer portals. We focus on reliability, cost control, and observability so your AI APIs perform consistently and transparently. Every project includes load testing, security hardening, and deployment infrastructure tuned to your traffic patterns. Our team has built AI APIs for SaaS platforms, marketplaces, and enterprise systems, and we bring that integration experience to every build.
How We Work — Our Process
A structured, transparent engagement model that ensures delivery quality at every step.
API Requirements & Design
We define the API scope, endpoints, data models, and integration patterns based on your application needs and the AI capabilities to be exposed.
1 weekAPI Architecture & Specification
We create OpenAPI specifications, design authentication and authorization flows, and define rate limiting, caching, and error handling strategies.
1-2 weeksCore API Development
We build the API server with model integration, request validation, streaming support, and async processing for long-running AI tasks.
3-4 weeksGateway & Multi-Model Routing
We implement multi-model routing, load balancing, fallback chains, and cost optimization logic across your chosen AI providers.
2 weeksSecurity & Rate Limiting
We add authentication, API key management, rate limiting, usage tracking, and security hardening to protect against abuse and ensure fair usage.
1-2 weeksDocumentation & SDK Generation
We generate API documentation, create SDKs for your target languages, and set up a developer portal with interactive examples and guides.
1-2 weeksWhy Choose Us
Our key differentiators that set us apart in the AI services landscape.
Multi-Model Gateways
We build gateways that route requests across OpenAI, Anthropic, open-source models, and your custom models, optimizing for cost, latency, and quality.
Streaming & Async Support
Our APIs handle real-time streaming for token-by-token responses and async processing with webhooks for long-running tasks like batch inference.
Enterprise Security
We implement OAuth 2.0, API key management, request signing, rate limiting, and usage quotas to protect your APIs from abuse and unauthorized access.
Intelligent Caching
We add semantic caching layers that detect similar prompts and return cached responses, reducing model calls by 30-50% and cutting costs significantly.
Full Observability
Every API request is logged with latency, cost, model used, and token counts, giving you complete visibility into usage patterns and spending.
Auto-Generated SDKs
We generate SDKs in JavaScript, Python, Go, and Java from your OpenAPI spec, so your developers can integrate your AI APIs in minutes not days.
What We Offer
Detailed breakdown of each offering within this service category.
Custom AI API Design
Bespoke API design that exposes your AI model capabilities with clean endpoints, proper data models, and integration patterns tailored to your applications.
- OpenAPI specification document
- API server with validation and routing
- Request and response schema definitions
- Integration examples and guides
LLM API Wrappers & Proxies
Wrapper APIs around LLM providers that add caching, fallback logic, request transformation, content filtering, and usage tracking to your model calls.
- LLM proxy server with caching layer
- Fallback chain configuration across providers
- Content filtering and moderation middleware
- Usage tracking and cost attribution system
Multi-Model API Gateways
Gateways that route requests across multiple AI providers and models, optimizing for cost, latency, quality, and availability with intelligent routing logic.
- Multi-model routing gateway
- Load balancing and failover configuration
- Cost optimization and model selection logic
- Provider health monitoring and alerts
AI API Authentication & Rate Limiting
Authentication, API key management, rate limiting, and usage quota systems that protect your AI APIs and ensure fair resource allocation across users.
- OAuth 2.0 or API key authentication system
- Rate limiting with tiered quotas
- Usage tracking and billing integration
- Security hardening and abuse detection
AI API Documentation & SDKs
Auto-generated API documentation, SDKs in multiple languages, and developer portal setup to make your AI APIs easy to integrate and use.
- Interactive API documentation portal
- SDKs in JavaScript, Python, Go, and Java
- Code examples and integration tutorials
- Developer onboarding guides
Technology Stack
The tools, platforms, and frameworks we use to deliver this service.
| FastAPI | Python API framework | Expert |
|---|---|---|
| Express.js | Node.js API framework | Expert |
| OpenAPI / Swagger | API specification and docs | Expert |
| Kong API Gateway | Enterprise API gateway | Advanced |
| Redis | Caching and rate limiting | Expert |
| Nginx | Reverse proxy and load balancing | Expert |
| OpenAI API | LLM provider integration | Expert |
| Anthropic API | LLM provider integration | Expert |
| Grafana + Prometheus | Monitoring and metrics | Advanced |
| Docker + Kubernetes | Container deployment | Advanced |
Use Cases & Industry Applications
Real-world scenarios where this service delivers measurable business impact.
Engagement Timeline & Impact Metrics
Project Timeline
| Phase | Duration | Key Deliverable |
|---|---|---|
| Requirements & Design | 1-2 weeks | OpenAPI specification and architecture |
| Core Development | 3-4 weeks | Functional API with model integration |
| Gateway & Security | 2-3 weeks | Gateway, auth, and rate limiting |
| Docs & Deployment | 1-2 weeks | SDKs, documentation, and production deployment |
Business Impact
| Metric | Before AI | After AI |
|---|---|---|
| API Latency | 450ms | 120ms |
| Model API Costs | ₹4.2L/month | ₹2.1L/month |
| Cache Hit Rate | 0% | 38% |
| Integration Time | 2 weeks | 2 days |
| API Uptime | 97.5% | 99.9% |
Our Capabilities
| Capability | Status |
|---|---|
| Multi-model routing gateway | Available |
| Streaming and async support | Available |
| Semantic caching layer | Available |
| OAuth 2.0 and API key auth | Available |
| Auto-generated SDKs | Available |
| Usage tracking and billing | Available |
Pricing & Packages
Transparent pricing for every engagement size. All packages include post-delivery support.
| Tier | Price | Timeline | Includes |
|---|---|---|---|
| Starter | ₹49,000 | 2-4 weeks | Single API, basic auth, OpenAPI spec, 1 SDK |
| Growth | ₹1,29,000 | 5-7 weeks | Multi-model gateway, caching, rate limiting, 3 SDKs |
| Enterprise | ₹2,99,000 | 8-12 weeks | Full API platform, SSO, billing, developer portal, all SDKs |
What Is Included
- API requirements analysis and design
- OpenAPI specification and documentation
- API server with model integration
- Authentication and rate limiting implementation
- Caching and cost optimization layer
- SDKs in your target languages
- Interactive API documentation portal
- 30 days post-launch support and monitoring
If your AI API does not meet the agreed latency and uptime targets within 30 days of deployment, we provide free optimization iterations until it does.
Book a Free Consultation
Speak with our AI experts about your specific requirements. We will assess your needs, recommend the right approach, and provide a detailed proposal within 48 hours.
Book Your Free Consultation →Frequently Asked Questions
What is an AI API gateway and why do I need one?
An AI API gateway sits between your applications and AI model providers, handling routing, caching, authentication, rate limiting, and fallback logic. You need one to control costs, ensure reliability, add security, and avoid vendor lock-in by abstracting provider differences behind a unified interface.
Can you build APIs around multiple AI providers?
Yes. We build multi-model gateways that integrate OpenAI, Anthropic, Google, open-source models, and your custom models. The gateway normalizes request and response formats, routes based on cost or quality preferences, and provides automatic failover when a provider has an outage.
How does semantic caching reduce my AI API costs?
Semantic caching detects when incoming requests are similar to previously answered ones and returns cached responses instead of calling the model again. This typically reduces model API calls by 30-50% for applications with repetitive query patterns, directly lowering your costs.
Do you provide SDKs for the APIs you build?
Yes. We generate SDKs from your OpenAPI specification in JavaScript, Python, Go, Java, and other languages. These SDKs handle authentication, request serialization, error handling, and streaming, so your developers can integrate your AI APIs quickly and reliably.
How do you handle streaming responses in AI APIs?
We implement Server-Sent Events (SSE) or WebSocket endpoints that stream token-by-token responses from LLMs to your applications. This enables real-time text generation UX where users see responses as they are generated, rather than waiting for the complete response.
Can you add billing and usage tracking to our AI API?
Yes. We implement usage tracking that records token counts, model used, latency, and cost per request. We integrate this with billing systems to support usage-based pricing, tiered plans, and per-tenant cost attribution for multi-tenant platforms.
How do you secure AI APIs against abuse?
We implement multiple layers including API key management, OAuth 2.0, rate limiting per user and per endpoint, request size limits, content filtering, IP-based restrictions, and anomaly detection. For public APIs, we add CAPTCHA and WAF protection against automated abuse.
Can you deploy the API on our infrastructure?
Yes. We deploy on your cloud accounts (AWS, GCP, Azure), on-premise servers, or hybrid setups. We use Docker and Kubernetes for portable deployment, and configure auto-scaling, load balancing, and monitoring for your specific traffic patterns.
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