Sixb

Sixb

Sixb is a TypeScript framework for building ontology-powered applications and AI, providing connectors, dataset syncs, pipelines, a shared object model, queries, workflows, agents, and SDKs to turn integrated data into apps and automated actions.

Sixb is ai agents software teams evaluate for software & gaming. Use this page to review pricing, integration signals, and the best alternatives before you commit.

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#556 in AI Agents (556 tools)
Just launched
Data reviewed Sep 27, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: Software & Gaming

What it does

AI Agents software for decision-makers comparing workflow fit and alternatives.

Best fit

Software & Gaming

Pricing snapshot

Pricing available on request

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Sixb

Sixb is a TypeScript-first framework designed to power applications and AI workflows around a shared ontology. It provides a full-stack set of building blocks — connectors to external systems, typed datasets and syncs, pipelines for data preparation, object types (ontology) and projections, query capabilities, AI/agent integration, workflows and actions, client SDKs, and runtime/operation tools (CLI, HTTP API, WebSockets). Sixb targets developers and teams who want to centralize data from multiple sources into a typed model and use that model consistently across apps, agents, and automation.

Model your domain. Put it to work. A TypeScript framework for ontology-powered apps and AI.

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Key Features

Connectors library

Prebuilt connector pattern and examples (e.g., Pipedrive) with defineConnector to bring external systems into your project.

Datasets & Syncs

Define typed datasets (defineDataset) and configure syncs to ingest rows from connectors into the project.

Pipelines & Data Preparation

Define pipeline steps and SQL/TypeScript transformations to clean and shape raw datasets into usable data for the model (definePipeline, definePipelineStep).

Ontology & Object Types

Define object types and properties (defineObjectType, prop) to create a shared typed model (the ontology) for apps and AI.

Queries & Client SDK

Typed query API and client hooks (useObjectsQuery, objects(...).query()) to fetch model data from the runtime.

Workflows & Actions

Define workflows (defineWorkflow) that sequence steps, include human approvals, and run actions that can write back to external systems.

AI & Agents

Integrated AI capabilities, agent scaffolding, models, sandboxes, and tools to incorporate AI prompts and assistants in workflows and apps.

Runtime & Deployment

Local development and deployment CLI commands (bun sixb dev, bun sixb build, bun sixb api) plus HTTP API and WebSocket access for integrations.

Security & Access Control

Role, group, and grant constructs to define who can see data and invoke operations, supporting members, service accounts, and shared access.

React & TypeScript App Integration

Examples showing React pages using the same object model and client hooks to render application UIs alongside agents and automation.

Pricing

Current pricing details are not available from the vendor source.

Use Cases

Connected business apps

Integrate multiple external systems (CRM, file storage, document systems) into a single ontology so apps and agents work from a unified model.

Automated approvals and actions

Define workflows that gather data, pause for human review, then run actions that write back to external services (e.g., creating a contract in PandaDoc).

Data preparation and modeling

Ingest raw datasets, run pipeline transformations, and project rows into typed object models for consistent querying and AI usage.

AI-assisted agents and summarization

Query model data and feed results into AI prompts or agents to summarize, explain, or recommend actions.

Integrations

Pipedrive

Example connector integration used in docs to sync CRM customers into datasets and the shared model.

PandaDoc

Used in the example flow to create documents from model actions (example shows sending actions back to PandaDoc).

CompanyCam

Listed as a connected system in the Northline example for sharing site and customer data.

Google Drive

Included in the example integrations to illustrate connecting file storage into the shared model.

Benefits

Unified typed model reduces integration complexity and enables consistent app, AI, and automation logic.
TypeScript-first approach and client SDKs provide type safety and developer productivity.
Built-in connectors and pipeline primitives accelerate data ingestion and preparation.
First-class workflow and action primitives let you automate end-to-end processes including human approvals.
Multiple runtime access patterns (CLI, HTTP API, WebSockets, SDK) support diverse deployment and integration needs.

Limitations

No verified limitations are available.

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Step 1: Read the setup guide at https://docs.sixb.ai/README.md and relevant LLM guidance at https://docs.sixb.ai/llms.txt.
  2. 2 Step 2: Scaffold a project with Bun: run bun create sixb <project-name>, enter the project directory, and run bun install.
  3. 3 Step 3: Follow the generated project instructions, define your shared TypeScript model, connect data sources via connectors, and start the local runtime with bun sixb dev.

Support

docs

Primary documentation and guides available at https://docs.sixb.ai/.

examples

Live example projects and a referenced GitHub example are linked from the documentation (Open example on GitHub).

CLI

Local development and operational commands are provided in docs (bun sixb dev, bun sixb build, bun sixb api).

API

Available: Yes
Documentation:

Documentation for HTTP API and WebSocket access is available in the docs at https://docs.sixb.ai/.

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