1. Observe
Trace every prompt, logic branch, and token cost in real-time. No hidden operations.
OBTO is the first transparent architecture for Agentic AI. Build, observe, and scale AI workflows without data lock-in. Run it managed in our cloud today, or take it entirely in-house onto your own Kubernetes clusters tomorrow.
No seat taxes. Pay only for the compute and tokens your agents use.
Trace every prompt, logic branch, and token cost in real-time. No hidden operations.
Standardize how your models talk to your data using the open Model Context Protocol (MCP).
Build autonomous Agentic workflows with visual guardrails and versioned deployments.
Containerized by default. Seamlessly migrate your entire AI runtime from our SaaS to your infrastructure.
Deploy agents that can reason, access your internal APIs, and execute complex workflows securely.
Build, host, and monitor standardized MCP tools that any major LLM can interact with.
Custom apps to handle ITIL/ITSM requests, ticketing, and service ops with an AI copilot.
Extract, transform, and load data using LLMs to normalize messy inputs automatically.
Customer or employee portals featuring role-based access to your tailored AI assistants.
Real-time dashboards exposing the cost, performance, and decisions of your Agentic network.
Start fast on our managed cloud. When compliance or cost demands it, shift your workloads to your own Kubernetes infrastructure with zero code changes.
Connect to ServiceNow, databases, and internal APIs using the Model Context Protocol. No more brittle, proprietary vendor connectors.
You built the workflow, it belongs to you. We provide the engine and the built-in storage, but you retain full ownership of your IP and logic.
True intelligence shouldn't be hidden behind a proprietary API. OBTO forces AI to show its work, giving enterprises the observability they need to trust autonomous agents in production.
Transparent, AI-assisted learning and tutoring flows for universities.
Agentic copilot for ServiceOps. Resolve IT tickets with fully audited actions.
Design, publish, and observe MCP tools for any LLM. Version-controlled.
The core runtime to build, monitor, and scale transparent AI apps.
Run OpenAI, Groq, Ollama, and open-weights models side-by-side.
Compose tool-using agents with strict, auditable guardrails.
Built from the ground up to support the Model Context Protocol.
Secure execution environments with built-in logging and evals.
Design purpose-built agents for research, automation, and ETL. Deploy them with versioned releases, enforce strict policy guardrails, and track every action with the Glass Box dashboard.
A complete, opinionated runtime for Agentic apps. Designed for the enterprise that wants speed today, and total architectural ownership tomorrow.
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The "Glass Receipt" ensures you never wonder why an agent made a decision or what it cost.
Embrace MCP to break free from proprietary tool-calling silos.
Containerized architecture means your workflows can migrate in-house seamlessly.
Policy sandboxing and deep audit trails protect your enterprise data.
No arbitrary seat licenses. No hidden model markups. You pay strictly for the compute and tokens your agents consume. Start free, scale predictably.
We meter tokens, requests, and storage like a true utility. You get a "Glass Receipt" showing exactly what models cost you what amounts.
Yes. Our Enterprise plan is built for Hybrid deployment. You can port the runtime entirely to your own private cloud or bare metal servers.
Any OpenAI-compatible endpoint, plus local open-weight models. We use the Model Context Protocol (MCP) to standardize tool connections.
Visibility doesn't mean vulnerability. We never train on your data, all connections are encrypted, and we enforce strict Role-Based Access Controls.
Deploy your first observable Agentic workflow today. Scale transparently tomorrow.