ChatWith provides a low‑code platform for enterprises to design, train, and deploy custom large‑language‑model chatbots without extensive coding. The solution includes a visual conversation builder, pre‑integrated LLM APIs, auto‑scaling serverless runtimes, native connectors for web, mobile, and messaging channels, and real‑time analytics with compliance‑ready data handling.
Funding
$849.6K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
ACFounders
Product
Problem
Businesses often lack the technical resources and infrastructure to develop, train, and maintain large‑language‑model (LLM) powered chatbots, leading to fragmented customer support experiences across web, mobile, and messaging channels. Integration complexity and the need for continuous model tuning increase operational costs and delay time‑to‑value for conversational AI initiatives.
Solution
ChatWith delivers a low‑code platform that streamlines the end‑to‑end lifecycle of custom AI chatbots. Users design dialogue flows through a visual builder, select from pre‑integrated LLM providers, and configure context handling without writing extensive code. The platform automatically provisions scalable cloud runtimes and exposes native connectors for popular digital channels (website widgets, WhatsApp, Facebook Messenger, Slack, etc.). Real‑time analytics and A/B testing tools enable continuous performance monitoring and rapid iteration. All interactions are encrypted and stored in compliance‑ready data stores, allowing enterprises to deploy intelligent agents while maintaining security and governance.
Target Audience
Primary customers are mid‑size to large enterprises—e.g., e‑commerce retailers, SaaS providers, and contact‑center operations—that need to automate customer support and engagement across multiple digital touchpoints.
Features
- Drag‑and‑drop conversation designer with conditional logic, slot filling, and fallback handling
- Built‑in integrations with leading LLM APIs (OpenAI GPT‑4, Anthropic Claude, Cohere) and option for custom model endpoints
- Multi‑channel deployment kit offering SDKs and web widgets for web, iOS/Android, and major messaging platforms
- Context management layer supporting session persistence, user attributes, and dynamic knowledge base lookups
- Auto‑scaling serverless execution environment with usage‑based billing and latency SLA monitoring
- Dashboard with real‑time metrics, sentiment analysis, and conversation replay for continuous improvement
- Role‑based access control and audit logging to meet enterprise security and compliance requirements
- RESTful API and Webhook framework for seamless integration with CRM, ticketing, and analytics systems