Introduction

The Mindset API and SDK provide a powerful platform for developers who want to build AI-powered applications without the complexity of managing AI infrastructure.

The API gives you programmatic access to upload content, manage knowledge contexts, configure agents, and track analytics - everything you need to power intelligent applications.

The SDK provides pre-built JS components and utilities that let you embed multi-media, conversational agents into your application with just a few lines of code - no need to build chat interfaces from scratch.

So why do you need this - why not just work with one of the agent frameworks or the LLM directly?

Of course, that is an option, but the Mindset API and SDK provide a more streamlined and efficient way to work, where much of the heavy lifting is already done for you.

This allows you to focus on building your application and delivering value to your users, rather than worrying about the plumbing.

”But agents are just prompts, data, and configuration, right?”

Yes, at the surface level, an agent might look like a fancy chatbot with some prompts and a knowledge base. But that’s like saying a car is just an engine, wheels, and a steering wheel. Technically true, but you’re missing about 99% of what makes it actually work in the real world.

Here’s what you’re really building when you create production-ready agents:

  • Context Management: How do you maintain conversation state across sessions? What happens when users switch topics mid-conversation? How do you handle context windows that overflow?
  • Retrieval Engineering: Sure, you can throw documents at a vector database, but how do you handle conflicting information? How do you ensure the agent retrieves the right context, not just similar context?
  • Safety & Guardrails: What happens when your agent hallucinates? How do you prevent prompt injection? What about when users try to jailbreak your carefully crafted prompts?
  • Performance at Scale: Your prototype works great with 10 users. What about 10,000? How do you handle rate limiting, caching, and cost optimization across multiple LLM providers?
  • Tool Orchestration: Agents that can only chat are toys. Real agents need to trigger actions, call APIs, and orchestrate complex workflows. How do you handle tool failures, retries, and partial completions?
  • Observability: When your agent gives a wrong answer, how do you trace it back through the retrieval pipeline, prompt construction, and model reasoning to figure out what went wrong?

The difference between a weekend hackathon agent and a production system is the same as the difference between a paper airplane and a Boeing 747. They both fly, but only one will get you where you need to go reliably.

Do you really want to build the following yourself?

  • Content Management: Uploading, managing, and organizing content efficiently and making it available to agents ensuring the right users see only the right content.
  • Knowledge Contexts: Ingest, organize, and manage content libraries for agents, including integration with external sources.
  • Label Management: Creating and managing labels for content classification and ensuring that every agent interaction is properly tracked and categorized.
  • Analytics & Reporting: Track agent performance, usage, and user interactions with built-in BI dashboards and reporting tools.
  • Testing Environment: Comprehensive testing framework with the ability to manage agent test configurations across different LLMs and compare performance results.
  • Tool Integration: Enable agents to use tools (like clarification or URL injection) and manage tool invocation logic automatically.
  • Policy & Guardrails: Configure agent policies, guardrails, and safeguards to control agent behavior and ensure compliance.
  • Bias Analysis: Automatically analyze agent knowledge for unexpected or risky concepts and trace them to their source.
  • Multi-Tenant Management: Support for multiple tenants, each with their own agents, knowledge, and analytics.
  • Human/User Management: Securely manage users (humans) and accounts with advanced authentication and privacy controls.
  • Integrations: Out-of-the-box integrations with 500+ apps and services via a low-code GUI and embedded iPaaS.

Surely you would rather focus on the good stuff

  • Building Your Core Product: Focus on what makes your application unique instead of rebuilding AI infrastructure from scratch.
  • Seamless Agent Integration: Embed intelligent agents into your application with just a few lines of code, complete with customizable UI components.
  • Rapid Prototyping & Deployment: Go from concept to production in days, not months, with pre-built components and workflows.
  • Leveraging 500+ Integrations: Connect to CRMs, payment systems, communication channels, and content sources through our embedded iPaaS without building custom connectors.
  • Creating Exceptional User Experiences: Design engaging, conversational interfaces that your users will love, backed by enterprise-grade AI capabilities.
  • Building for the Future of Interfaces: Prepare for a world where software is consumed through minimal interfaces - voice commands, ambient computing, and eventually just an earpiece.
  • Voice-First Applications: Develop applications that work seamlessly with voice interactions, reducing the dependency on traditional screens and keyboards.
  • Ambient Intelligence: Create software that integrates naturally into users’ environments, anticipating needs and responding through the most natural interface possible - conversation.
  • Scalable Architecture: Build applications that grow with your business, supported by our multi-tenant, cloud-native infrastructure.
  • Innovation Over Infrastructure: Spend your time solving customer problems and creating value, not managing servers, databases, and AI model configurations.

The Bottom Line

While you could spend the next 6-12 months building your own AI infrastructure, wrestling with vector databases, prompt engineering at scale, and debugging mysterious agent behaviors at 3 AM, we’ve already solved these problems already.

The Mindset platform handles the complex, boring stuff so you can focus on what you’re actually good at - building amazing products that users love.

Ready to get started? Let’s dive into the API and SDK documentation.