Embed ‘Chat With Your Data’ Using camelAI API & iFrame in Under 30 Minutes

This post is a great place to start but for details read our API & iframe docs: camelai.com/docs

Embedding AI analytics directly into your SaaS product is rapidly shifting from a differentiator to an essential capability. As users demand instant, self-serve data insights in plain language, having an AI analyst within your platform isn’t just a nice-to-have—it’s quickly becoming a must. Building and maintaining this functionality from scratch is complex and time-consuming, but with camelAI’s API and iframe offering, you can add a fully-featured “chat with your data” experience out of the box—no months-long development cycles required.

Why Embedded AI Analytics Is Becoming Essential in SaaS

The SaaS landscape is evolving at an unprecedented pace. Business users expect real-time access to data-driven insights without waiting on technical teams or learning SQL. This shift is more than just a trend—embedded analytics is now considered critical for product stickiness and user satisfaction.

According to Gartner, by 2025, 75% of enterprise-generated data will be created and processed outside a traditional data center or cloud, driving demand for embedded analytics. Organizations across sectors are recognizing the strategic advantage of AI-powered analytics, with a 2024 survey by Dresner Advisory finding that 60% of organizations consider embedded analytics critical to their business success.

The market reflects this momentum. The global embedded analytics market is projected to reach \$77.52 billion by 2026, growing at a CAGR of 14.1%. For SaaS vendors, offering instant, conversational data exploration is becoming a baseline expectation—especially as 86% of SaaS companies plan to increase investment in AI-powered analytics features within the next 12 months.

For teams looking to deliver these experiences quickly, camelAI provides a turnkey way to meet user demand and keep pace with the market.

Overview: camelAI API and iFrame for Instant “Chat with Your Data”

camelAI is purpose-built to enable seamless AI analytics within any SaaS application. Its API and embeddable iframe deliver a robust, flexible solution for turning natural-language questions into actionable SQL queries and interactive visualizations, all within your product’s existing interface.

• API: The camelAI API exposes all the core capabilities of the camelAI agent, including iterative query refinement, knowledge base lookups, reference queries, and automatic chart generation. Features like thread management, real-time streaming with Pub/Sub, and transparent cost-plus pricing ensure that you can scale with confidence.
• Embeddable iFrame: For teams seeking the fastest path to production, camelAI’s iframe lets you drop a fully-featured, beautifully designed chat-with-your-data UI into your app with a simple embed. The iframe always stays at parity with the web app, so users benefit from the latest updates—no ongoing maintenance required on your end.

Both options connect directly to major databases (Postgres, MySQL, ClickHouse, Snowflake, BigQuery, Supabase, and more) or accept CSV uploads. camelAI’s agent translates user questions into SQL, executes them securely, and visualizes results using interactive Plotly charts. Each query (“thought”) is fully transparent for technical users, with modes to hide complexity for less technical audiences.

With camelAI, you can empower your users to generate new insights, explore data ad hoc, and reduce the engineering lift for custom dashboard requests—all in a matter of minutes.

Step-by-Step: Setting Up camelAI API and iFrame in Your Product

Integrating camelAI’s API or iframe is designed to be fast and developer-friendly. The process ensures secure, robust analytics while minimizing engineering overhead. Here’s how you can get started:

1. Access the Developer Console: Begin by using camelAI’s developer console. Here, you can perform CRUD operations for API keys, data sources, knowledge bases, and reference queries. You can also manage conversation threads for auditing and debugging purposes.

2. Connect Your Data Source: Link your database (Postgres, MySQL, ClickHouse, DuckDB, Snowflake, BigQuery, Supabase, or upload CSVs). Once connected, you can instantly preview your data source within the console—camelAI renders a live iframe preview so you can interact with your data in real time, using session authentication for security.

3. Generate API Keys: For production deployment, generate a secure API key via the console. This key will authenticate requests and ensure only authorized users can access your data through camelAI.

4. Embed the iFrame or Integrate the API:

   • iFrame: Use the code snippet provided in the developer console to securely generate an iframe link. You can configure the UI, control feature visibility, and ensure the iframe is styled to match your application. It’s fully sandboxed and production-ready.
   • API: Integrate the REST API endpoints for deeper control or to build a custom front-end. camelAI’s open source chat application is tailor-made for use with the API, compatible with next.js, node.js, and more.

   Here’s the typical JavaScript snippet to create a production-ready iframe:

   const options = {
    method: 'POST',
    headers: { Authorization: 'Bearer <token>', 'Content-Type': 'application/json' },
    body: '{"uid":"<string>","srcs":["<string>"],"ttl":900}'
   };
   
   fetch('https://api.camelai.com/api/v1/iframe/create', options)
    .then(response => response.json())
    .then(response => console.log(response))
    .catch(err => console.error(err));
   

5. Test and Iterate: Experiment with the embedded chat agent, customize response modes, and adjust the UX to fit your users’ needs. With camelAI, you can spin up instant AI analytics in under 15 minutes versus months of development if building from scratch.

The result? Your SaaS can offer instant, secure AI analytics without the ongoing maintenance burden.

Customization, User Experience Modes, and Branding

camelAI’s embeddable experience is engineered for maximum adaptability, allowing you to tailor both functionality and presentation to your audience's needs.

• UI Theming: Customize the color scheme, fonts, and toggle between light and dark mode to match your product’s branding guidelines.

• UX Configuration: Choose how much technical detail to show based on your users’ proficiency:

• Show all thoughts: Display every step—SQL queries, code, and rationale—ideal for technical users.

• Hide technical details: Suppress SQL and Python code, creating a “Lite” mode focused on explanations and summaries.
• Final answer only: Present just the final insight, with no intermediate details, for maximum simplicity.
• Feature Toggles: Enable or disable model switchers, chat recommendations, and other advanced options as appropriate for your user base.

This depth of customization lets you deliver an analytics experience that feels native and intuitive for every segment of your user population. Save on front-end development while retaining full control over how analytics are presented and consumed.

Security, Compliance, and Cost Transparency

Security and governance are core to camelAI’s design. As you embed AI analytics into your SaaS, robust safeguards ensure data privacy, compliance, and cost predictability:

• Authentication & Authorization: All API and iframe requests are authenticated with secure API keys. Session-based authentication secures preview environments, and row-level security (RLS) ensures users only access their own data.
• Automatic SQL Validation: camelAI’s agent interprets natural language, generates parameterized SQL, and exposes every query for review. This transparency helps mitigate risk and facilitates compliance with internal policies.
• Compliance Alignment: Data connections and artifact storage are managed with best-in-class security practices. Audit trails and thread logs are available for oversight and regulatory review.
• Cost-Plus Pricing: camelAI’s API is priced on a transparent cost-plus basis—25% markup on the tokens you use, with an additional monthly fee for iframe embedding. This makes budgeting straightforward and eliminates hidden costs.

Security concerns remain top of mind, with 94% of applications analyzed in 2021 found to be vulnerable to SQL injection attacks. camelAI addresses these challenges by integrating best practices in query validation and access control, helping you deliver safe, compliant analytics to your users.

Real-World Use Cases: How SaaS Teams Leverage Embedded AI Analytics

camelAI’s API and iframe are already powering advanced analytics in a variety of SaaS scenarios:

• Bank Transaction Cleansing: Financial SaaS providers embed camelAI so end-users can “chat with their data,” instantly exploring trends and anomalies in cleansed transaction records—no custom dashboard engineering required.
• Retail Returns Analytics: Retail analytics platforms use camelAI to handle one-off, ad hoc data requests from customers, letting them drill into return reasons and patterns without creating bespoke dashboards for every inquiry.
• Data Management SaaS: Any platform offering data insight or management can empower users to generate their own charts and metrics, reducing support tickets and accelerating time-to-insight.

These integrations solve the pain of constant feature requests for new dashboards or custom analytics, all while keeping engineering teams focused on core product development.

Conclusion: The Future of Embedded AI Analytics in SaaS

Embedded AI analytics is no longer a futuristic ambition—it’s a strategic necessity for SaaS providers. As user expectations rise and data volumes explode, delivering real-time, conversational analytics will define the winners in the space. camelAI’s API and iframe offering let you deliver this capability in minutes, not months, while maintaining security, transparency, and a native user experience. To see how quickly you can get started, visit https://camelai.com/api and discover the future of AI-powered analytics for your platform.