AI Agents

Talk to Your Apps and Documents: IA Agents at Your Service

Harness the power of Large Language Models to interact directly with your applications and documents. With Retrieval-Augmented Generation (RAG), real-time streaming, and function call access, IA Agents seamlessly integrate with your data to provide instant, intelligent responses. Whether it’s extracting information from documents or executing tasks in your apps, our agents transform them into active conversational partners, driving efficiency and automation like never before.

Function Calls

What defines an agent is the ability to call functions based on APIs. We are capable to call functions independent of the LLM model.

LLM Streaming

LLM streaming is essential for conversational AI. The ability to interrupt and to quickly start rendering new phrases is key.

LLM Agnostic

With our agent infrastructure you can switch between different LLM providers and even use Open Source models preserving the agent

Local Function Calls

Sometimes you need to send functions to the client such as when you need to transfer a call on a PBX

Thread Control

Control the session with the bot. You can terminate the session or keep the context of the conversation

Simulate the cost

Quickly create agents using our playground. Simulate the costs and latency of different models. 

WhatsAPP Integration

Easily integrate your bot with your WhatsAPP number

Restful APIs

We have REST APIs with examples in Curl, Python and Node.js

WebRTC

Use the agents via webrtc on your own website

Deployment models

Proxy Model

  • Fast and accurate proxy to OpenAI
  • Cost effective
  • Use best of breed providers available

Serverless

  • Use your favorite open source model
  • Best price per token
  • Total privacy
  • Low volume commitment

Instance

  • Best option for large volumes
  • Total privacy
  • Fixed and predictable pricing per month

High Speed

  • High performance Inference servers. 
  • Minimum volume required

Local

  • For large projects we can deliver the system locally