Everything you need to ship agents that take action.

01

Visual Agent Builder

Compose an agent the way you compose a document. Pick tools, write the system prompt with AI assistance, set guardrails, and preview answers against real fixtures — all in the browser.

Every agent is versioned. Branch a production agent, change one tool, A/B against the original, and promote when the metrics agree. No git required, but everything works the same way for engineers who want it.

• No-code builder with AI-assisted prompt drafting
• Versioning, branching, and one-click rollback
• Reusable skill library shared across agents
• Live preview against saved test conversations

02

Multi-Channel Deployment

Build the agent once. Deploy it to Slack as a bot, to a web chat on your docs, to a voice line over Twilio, or as an embeddable widget on a customer portal.

Channel-specific affordances are handled for you: thread context in Slack, SSML in voice, structured cards on the web. The agent's skills, memory, and corrections stay consistent across surfaces.

• Slack bot with thread-aware context
• Web chat widget with branded styling
• Voice agents over Twilio (inbound and outbound)
• Embeddable widget for product surfaces and docs

03

Sub-Agent Orchestration

Big problems decompose. A sales analytics agent can hand off to a contract-risk specialist, a renewal forecaster, and an upsell scout — each with its own tools and prompt — and synthesize a single answer.

Hand-offs are first-class: typed inputs and outputs, depth limits, and tracing across the entire call graph so you always know which sub-agent did what.

• Named hand-offs with typed I/O
• Configurable delegation depth (default 3)
• Full trace across the agent call graph
• Per-sub-agent tool and permission scopes

04

Knowledge Corrections

The model is generic. Your domain isn't. Knowledge corrections are how subject-matter experts pin the right answer to a question without retraining anything.

When a reviewer marks an answer wrong and writes the correct one, BeeKeeper indexes it semantically. Future questions that match the same intent retrieve the correction and the agent answers from your team's ground truth.

• In-line review and correction in any channel
• Semantic retrieval of past corrections
• Per-agent and per-team correction scopes
• Coverage reports show which questions still need expert input

05

Multi-Model Routing

No single model is best at everything. BeeKeeper routes each task to the model that fits — Claude for nuanced reasoning, GPT for high-volume summarization, Gemini for long context, an open-source model for cheap classification.

Bring your own keys for Anthropic, OpenAI, Google, and OpenRouter. Set fallbacks. Cap spend per agent.

• Anthropic, OpenAI, Google, OpenRouter supported out of the box
• Per-skill model selection with automatic fallbacks
• Spend caps and rate limits per agent
• BYOK — your usage stays on your contracts

06

Memory and Retrieval

Agents that work with people need memory. BeeKeeper gives every agent a persistent context store, a retrieval layer with re-ranking, and a curated set of training examples that ground its style.

Memory is scoped: per-conversation, per-user, and per-org. Nothing leaks across tenants. Everything is queryable and purgeable.

• Persistent conversation and user memory
• Hybrid retrieval (vector + keyword) with re-ranking
• Few-shot example library tied to skills
• Tenant-scoped, purgeable, audited

07

Connect to Anything (MCP)

BeeKeeper ships with deep first-party integrations for the systems your team already lives in: Slack, Salesforce, Jira, Confluence, GitHub, Google Workspace, Zendesk, Snowflake, Twilio, Sigma, Sage Intacct, Gong — and more.

Beyond that, BeeKeeper speaks Model Context Protocol natively. Point an agent at any MCP server — public or internal — and its tools become available the same way first-party tools are. That's how 100+ apps fits in one platform.

• ~24 deep first-party integrations with auth and pagination handled
• Native MCP client — drop in any MCP server
• Per-agent tool allowlists with audit trails
• Build internal MCP servers for proprietary systems