Many AI agents fail because they lack context or can’t handle complex tasks.

Our platform enables you to easily build AI agents that can comprehend your business data, utilize connected tools, and automate repetitive or complex tasks. These agents pull the proper context from your systems, databases, and even other AI agents, so their answers are accurate and useful.

Furthermore, they can communicate with people through text, voice, or video, providing quick and natural responses that often feel more effective than a human reply.

Behind the scenes, we utilize trusted technologies such as LangChain (to organize and connect AI actions), Hugging Face (to work with various AI models), and vector databases like Pinecone or Weaviate (to quickly find information). You can see what your agents are doing in real time, and the system continually learns from each interaction, so performance improves over time.

Example: If a customer requests to return a product, a basic AI agent might only provide information on the return policy. AI agents built on our platform can check the customer’s purchase history, verify product eligibility, and update the inventory system. Furthermore, it can process refunds through the payment gateway and send a confirmation email, all in one interaction. This will resolve the query instantly, improving efficiency and customer satisfaction.

Launching AI without proper testing can lead to serious errors, such as giving outdated information to customers, generating inaccurate compliance reports, or producing biased recommendations.

Our platform’s AI Testing & Evaluation feature enables you to test various AI models, including GPT-4, Cohere Command, and Llama 2, and determine the one that best suits your needs. You can also test prompts and set up retrieval-augmented generation (RAG) pipelines to improve how the AI finds and uses information.

Moreover, we combine automated checks with human reviews to ensure the AI is reliable, safe, and accurate before it is launched. Within the platform, you can create test cases, set clear success measures, and have subject matter experts review results. This approach lets you understand precisely how your AI will perform in the real world.

Example: If your AI generates financial summaries for clients, an untested system might miss recent transactions or miscalculate totals. Running it on historical data and cross-checking with verified reports will help catch errors early, ensuring accurate results from the very first day and maintaining client confidence.

Disconnected AI tools often create bottlenecks, as different systems work in isolation and require manual effort to transfer data between them.

Our platform solves this through API orchestration. It manages how your AI connects and communicates with other business applications, including marketing automation and sales CRMs, as well as compliance tracking and knowledge management systems.

We design custom architectures that ensure smooth, secure, and real-time integration, using trusted technologies such as REST and GraphQL APIs, middleware connectors, and event-driven services. This means your AI becomes an integral part of your workflows, rather than a separate, siloed tool.

Example: Suppose your sales team needs to follow up with a lead. Without connected systems, they may spend valuable time manually checking the CRM, campaign responses, and support tickets. However, AI can automatically consolidate this data, update the CRM with the latest activity, and alert the sales rep with a ready-to-use profile, helping them act faster and with better information.