AI Agent Studio
Teams underestimate what it takes to go from idea to production. What seems simple often turns into months of backend work. Building data pipelines, managing retrieval, fine-tuning prompts, debugging agent behaviour. Each step adds friction and cost.
The result is missed deadlines, half-built prototypes, and teams stuck stitching tools instead of shipping solutions.
Our low-code AI Agent Studio brings everything together. Use vectorised data, pre-built flows, and secure LLM hosting to design intelligent agents that work from day one.
With full control over tools, logic, and data access, Trismeg helps you move faster, reduce risk, and focus on what matters – delivering real value with AI.
Trismeg AI Agent Studio is a low-code platform for building, customising, and deploying intelligent agents at scale. Unlike rigid chatbots or generic assistants, it gives you complete control over how your agent thinks, speaks, and connects to your tools and data. Start with prebuilt agents for onboarding, support, or search. Customise every detail including personality, logic, prompts, and retrieval. Trismeg works with hosted and self-hosted language models, and can be deployed securely in the cloud or on your own infrastructure.
Enterprise customers can create and manage unlimited AI agents without restrictions.
- Start with pre-built agent templates for tasks like onboarding, support, search, and automation.
- Customise logic, tone, and tools through an intuitive visual interface.
- Connect agents to your vectorised data, APIs, and internal tools to give them real-time context and precision.
- Select the right LLM, configure prompts, and run evaluations to optimise agent performance before launch.
- Enable continuous learning with updated knowledge feeds and dashboards.
- Deploy agents in your cloud or on-prem infrastructure with full privacy and control.
- Scale to serve global teams and customers with high availability and low latency.
- Monitor performance and fine-tune behaviour using built-in analytics and dashboards.
- Enforce guardrails, approvals, and fallback paths to meet business and compliance needs.
- Run agents securely on your own infrastructure. Trismeg adapts to your cloud or on-prem setup without handling your data directly.
rismeg AI Agent Studio is a low-code platform for building, customising, and deploying intelligent AI agents that use vectorised data, integrated tools, and powerful LLMs. It gives teams full control over prompt flows, tool orchestration, and real-time behaviour. All without needing to write complex code.
Trismeg AI Agent Studio is low-code, but building effective agents still requires a solid understanding of AI concepts and data workflows. For teams that need support, Trismeg Innovation Services is available to help design, build, and launch high-impact agents quickly and confidently.
Yes. Every part of the agent is configurable – from tone of voice and system prompts to action logic and fallback behaviours. You can even plug in external APIs or internal databases to give your agent real-time context and capabilities.
Agents use vectorised data prepared through Trismeg’s ingestion pipeline. You can connect databases, drop documents, or sync data through APIs and WebSockets. Our system handles text extraction, chunking, enrichment, and semantic indexing for you.
You do. Trismeg runs in your environment, whether cloud or on-prem, giving you full control over data access, retention, and compliance. No data leaves your infrastructure unless you choose to integrate third-party services. This means your security, privacy, and regulatory standards are always enforced on your terms.
Trismeg supports hosted and self-hosted LLMs, including Anthropic, OpenAI, Meta, Deepseek, Mistral, Google, and others. You can test multiple models, compare outputs, and select the one that fits your needs for performance, privacy, and cost.
You get a real-time dashboard for tracking usage, performance, and feedback, including token and cost monitoring for hosted LLMs. The platform supports human-in-the-loop review and fine-tuning so you can iterate with confidence, improve accuracy, and meet evolving business needs.
MCP (Modular Connection Protocol) is Trismeg’s flexible integration layer that lets your AI agents securely interact with internal APIs, databases, and tools. With MCP, agents can retrieve real-time data, trigger actions, and stay aligned with your existing systems, without hardcoding connections or complex middleware.