Back to Services
API Integration

Enterprise LLM Integration

Integrate OpenAI, Anthropic, or open-source models into existing systems. API design, authentication, and rate limiting for production use. Production-ready in weeks.

4-6
Weeks to Production
20+
Integrations Delivered
99.9%
API Uptime
0
Data Breaches

Calling an API is easy. Building production integrations is not.

Any developer can make an API call to OpenAI. But production LLM integrations require much more: handling rate limits gracefully, managing costs across teams, ensuring security and compliance, monitoring for issues, and maintaining consistent performance.

Without proper architecture, teams end up with scattered API keys, no visibility into usage, surprise bills at month-end, and fragile integrations that break when providers have issues.

We build the integration layer that makes LLMs a reliable, governed, and cost-effective part of your technology stack. A foundation you can build on confidently.

What We Build

The complete integration layer between your applications and LLM providers.

API Gateway & Abstraction

A unified API layer that sits between your applications and LLM providers. Switch between GPT-4, Claude, or Llama without changing application code.

  • Provider-agnostic interface
  • Automatic failover between providers
  • Cost optimization through routing
  • Centralized prompt management

Authentication & Authorization

Secure access to LLM capabilities across your organization. Role-based access, usage quotas, and audit logging for compliance.

  • SSO/SAML integration
  • Per-user and per-team quotas
  • API key management
  • Complete audit trail

Rate Limiting & Cost Control

Prevent runaway costs and ensure fair usage. Intelligent rate limiting that respects provider limits while maximizing throughput.

  • Budget alerts and hard limits
  • Token-based rate limiting
  • Priority queuing for critical requests
  • Usage analytics and reporting

Reliability & Resilience

Production-grade reliability patterns. Automatic retries, circuit breakers, and graceful degradation when providers have issues.

  • Automatic retry with backoff
  • Circuit breaker pattern
  • Request timeouts and cancellation
  • Health monitoring and alerting

Common Scenarios

We work with companies at different stages of their AI journey.

Adding AI to an Existing Product

You have a working product and want to add AI capabilities. We integrate LLM features into your existing architecture without disrupting what works.

Examples:

  • AI-powered search in your knowledge base
  • Smart suggestions in your editor
  • Automated summaries in your dashboard
  • Natural language queries for your data

Building an AI-First Application

Starting fresh with AI at the core. We design the integration layer from day one to support rapid iteration on prompts and models.

Examples:

  • AI copilot applications
  • Generative content platforms
  • Intelligent automation tools
  • Conversational interfaces

Enterprise AI Governance

Rolling out LLM access across a large organization. We build the infrastructure for safe, compliant, and cost-effective AI adoption.

Examples:

  • Internal GPT interfaces
  • Prompt libraries and governance
  • Usage monitoring and chargebacks
  • Data loss prevention controls

User Experience Patterns

LLM responses take time. Great UX makes that time feel shorter and builds trust.

Streaming Responses

Token-by-token streaming for instant perceived responsiveness. Users see answers forming in real-time rather than waiting for complete responses.

Progress Indicators

Show reasoning steps, retrieval status, and generation progress. Transparency builds trust in AI outputs.

Cancellation Support

Allow users to cancel long-running requests. Stop token generation mid-stream to save costs and improve UX.

Provider Selection

Each LLM provider has trade-offs. We help you choose based on your requirements and can build multi-provider architectures.

OpenAI

GPT-4o, GPT-4 Turbo, GPT-4, o1
Strength: Most capable general-purpose models. Best for complex reasoning and broad knowledge.
Consider: Usage-based pricing can be unpredictable. Data sent to OpenAI servers.

Anthropic

Claude 3.5 Sonnet, Claude 3 Opus
Strength: Strong safety features. Excellent for long-context tasks (200K tokens).
Consider: Smaller ecosystem. Less third-party tooling.

Azure OpenAI

GPT-4o, GPT-4, GPT-3.5
Strength: Enterprise compliance (HIPAA, SOC2). Data stays in your Azure tenant.
Consider: Approval required. Model availability lags behind OpenAI.

Open Source

Llama 3.1, Mistral, Mixtral
Strength: Full control. No per-token costs. Data never leaves your infrastructure.
Consider: Requires GPU infrastructure. Less capable than frontier models.
Security First

Enterprise-Grade Security

LLM integrations handle sensitive data. We build with security as a foundation, not an afterthought.

  • Data Protection: Encryption in transit and at rest. PII detection and redaction. Configurable data retention policies.
  • Access Control: SSO integration. Role-based permissions. Granular API scopes.
  • Audit & Compliance: Complete request logging. Usage analytics. SOC2 and GDPR-ready.
  • Content Safety: Input/output filtering. Prompt injection prevention. Policy enforcement.

Compliance Ready

Our integration patterns are designed for regulated industries.

SOC 2 Type II
GDPR Compliant
HIPAA Ready
ISO 27001 Aligned

Built on Proven Patterns

We use battle-tested frameworks and patterns for API development. No experimental tech in production, no vendor lock-in.

The result is an integration layer your team can maintain and extend long after our engagement ends.

Technologies We Use

OpenAI API
Anthropic API
Azure OpenAI Service
LangChain / LangGraph
FastAPI / Express
Redis (caching/queuing)
PostgreSQL
Kong / NGINX

Ready to add LLM capabilities to your product?

Let's discuss your integration needs and design a solution that scales with your business.

Get in touch