PLATFORM

Your agent has the intelligence. Now let it execute.

Go from chatbot to general-purpose agent in five lines of code, with the product surfaces, execution controls, and operator visibility teams need to ship with confidence.

AGENT BOOTSTRAP
tools = session.tools()
agent = Agent(
  name="Assistant",
  tools=tools,
)
Support AgentResolved GH-482
Email AgentLabeled 3 emails
Slack AgentSummarized #engineering
SQL AgentRan analytics query
Code ReviewReviewed PR #127
Research AgentFound 12 sources
Built for authenticated agentsOperator-ready execution surfacesSecurity-first deployment options

Tools and integrations

Give agents access to the systems your teams already depend on without stitching together brittle custom adapters.

Execution engine

Move from tool lists to real actions with execution plans, sandboxed steps, and visible operator controls.

Auth and user context

Keep every session tied to the right user, the right accounts, and the right permissions as workflows scale.

PRODUCT SURFACES

The operator layer around every agent action.

Search tools

Filter the right actions for the task without overwhelming the model with irrelevant surface area.

Execution plan

Review what the agent is about to do before it touches external systems or real data.

Manage connections

Keep user-level auth state visible so the platform knows what each workflow can safely execute.

Operator approvals

Insert human checkpoints for sensitive actions so teams can approve, reject, or redirect live workflows.

Sandbox and operator logs

Run tool code in isolated environments with execution traces, outputs, and durable operator visibility.

Audit history

Track every tool call, auth decision, and workflow outcome in a durable record operators can review later.

platform.bellowa.com
bellowa_search_tools
Search the right tools for the task at hand.
Execution Plan
Authenticate user → Create page → Post to Slack
Manage Connections
Slack ✓ connected · Notion ✓ connected
Sandbox
Ephemeral execution with operator-visible results and logs.
SDK ENTRYPOINT
PythonTypeScript
session = bellowa.create(user_id="user_123")
tools = session.tools()
conn = session.authorize("github")

Five lines to real execution

Start with a session, resolve tools, and hand them to your agent stack without rebuilding auth or integration plumbing.

Framework agnostic

Use OpenAI, Anthropic, LangChain, CrewAI, MCP clients, or your own orchestration layer without changing the platform model.

Context-aware sessions

Each session carries its own auth state, tool surface, and workflow context so your agents do not start from scratch.

SECURITY AND DEPLOYMENT

Controls that keep platform execution trustworthy.

Team controls and RBAC

Designed for teams that need stronger boundaries, clearer auditability, and deployment models that fit how they already operate.

Zero-day log retention options

Designed for teams that need stronger boundaries, clearer auditability, and deployment models that fit how they already operate.

SOC 2 and ISO-minded operating model

Designed for teams that need stronger boundaries, clearer auditability, and deployment models that fit how they already operate.

Bring your own cloud deployment

Designed for teams that need stronger boundaries, clearer auditability, and deployment models that fit how they already operate.

FAQ

Questions teams ask before rolling the platform out.

How quickly can teams integrate Bellowa into an agent stack?

Most teams can get from first session to real tool execution in hours, then expand into broader operator workflows as they harden production paths.

Does the platform support both MCP and SDK-driven workflows?

Yes. The platform is designed to support MCP client flows as well as direct SDK and application-driven orchestration patterns.

How are auth and user-session contexts managed?

Bellowa keeps auth scoped to the right session and user context so agents execute with the intended tools, accounts, and permissions.

What deployment and security models are available?

The platform supports security-forward deployment patterns, including strong controls, auditability, and private infrastructure options for teams that need them.

Build the execution layer your agents have been missing.