LLMs unlock unparalleled functionality, but moving AI solutions from prototype to production comes with unique technical demands. Streaming responses must remain fast and coherent. Multi-step agentic workflows are needed to orchestrate between AI calls and your existing systems. Rate limiting and cost controls must be in place to prevent runaway expenses. Security safeguards must protect sensitive data while maintaining compliance.
Since 2010, AgilityFeat has specialized in integrating complex platforms like AWS, Azure, Google, Twilio, Stripe, and Salesforce into production-ready software products. Our nearshore development teams across Latin America have delivered HIPAA-compliant telehealth solutions, sign-language enabled video support, and scalable edtech platforms serving thousands of students.
LLM integration is the next evolution and we’re leading the way. In our new white paper, we reveal the proven architectural patterns and integration strategies our teams use to move LLM-powered features from prototype to production.
What You’ll Learn in This New White Paper
- Agentic workflow patterns to connect LLMs with your APIs and databases
- Streaming architectures for rapid, coherent user experiences
- Cost-control scaling strategies for growth from dozens to thousands of users
- Prompt engineering methods to boost accuracy and reduce hallucinations
- Security and compliance frameworks for safe, reliable AI deployment
Download AgilityFeat’s white paper to access actionable implementation patterns, architecture diagrams, and real-world code examples. Bring your AI roadmap to life with field-tested guidance from experienced integration partners.
