Guanta
Guanta is an AI process platform that lets enterprises build, run, and track AI agents connected to their business knowledge, systems, and workflows. The platform combines agent infrastructure, observability, security controls, and a built-in database with a forward-deployed engineering team that customizes the system for specific production use cases like customer support or document-heavy operations. It supports cloud or on-premise deployment with options for running LLMs inside customer infrastructure.
- Artificial Intelligence
- AI Agents
- Enterprise Software
- Software Only
Funding
Founders
Product
Problem
Enterprises rely on a hidden digital operating system of emails, spreadsheets, manual approvals, and disconnected software, which forces employees to act as middleware between applications. Standard business software cannot fully encode each company's unique workflows, so teams fill the gaps with repetitive, document-heavy, and rule-driven manual work that is expensive and error-prone.
Solution
Guanta provides an AI process platform that lets companies build and operate complete AI-assisted processes, not just isolated automations. The platform includes a reusable production layer for creating agents, connecting data and integrations, executing workflows, and tracking outcomes, which is extended by a forward-deployed engineering team that adapts it to each customer's specific systems, controls, and edge cases. Guanta combines configurable agents, observability tools, scoped security, a built-in database, and an AI-coding environment so that processes can be launched in production with human review and measurable results. The company's FDE capability means customers do not need to hire or train their own deployment engineers to get value.
Target Audience
Guanta targets mid-to-large enterprises with complex, document-heavy, or system-mediated operational workflows in areas such as customer and patient support, compliance, finance, and internal tooling that need production-grade AI automation.
Features
- Agent runtime with configured prompts, knowledge sources, tools, objectives, and controlled execution for AI-assisted work
- Full observability with traces, interaction history, evaluations, intent maps, performance views, and review workflows
- Security model including scoped agent access, private knowledge sources, authentication, and deployment options for cloud or on-premise
- Built-in database for structured state, operational records, application data, and process history owned by the workflow
- Integration layer for APIs, CRMs, ERPs, internal tools, documents, browser automation, and data pipelines
- AI-coding environment for building custom screens, workflows, tools, and process-specific software faster
- Forward-deployed engineering capability that extends the platform into customer workflows and turns field learning into reusable product leverage