How much does Redbird cost?

No public pricing; demo request and AWS Marketplace listing. Enterprise analytics platform sold via a sales led motion; turnkey on premises deployments are offered for security sensitive customers.

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Redbird

Q: Who is Redbird for?

Enterprise data and analytics teams, Marketing and operations teams, Fortune 50 brands and government organizations

Also known as: Redbird AI, Cube Analytics

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Data analyst agentindependentVerified 2026-07-08

Conversational analytics platform whose specialist AI agents automate the full data lifecycle, from collection and wrangling to data science and reporting, with full auditability and on prem LLM options.

Redbird is an AI powered, conversational analytics platform that automates analytics, operations, and reporting work for business teams. A routing agent interprets a natural language prompt and dispatches specialist agents, such as a Data Engineering Agent, Data Science Agent, and PowerPoint Reporting Agent, each of which identifies relevant datasets and executes its part of the pipeline using Redbird's underlying toolkit. The company says its agents can handle more than ninety percent of an enterprise's business intelligence work, spanning data collection, wrangling, advanced analytics, data science, and reporting without a single manual SQL query, workflow configuration, or dashboard build.

Every data pull, transformation, calculation, and output is logged and inspectable, so nothing is a black box, and users can modify agent built steps through a point and click no code interface or code edits without rebuilding from scratch. Self healing agents detect and fix steps that break when data, APIs, or interfaces change, and an admin layer lets domain experts load data ontologies, business logic, and reporting blueprints so central teams keep governance control over the answers shared across the organization.

Founded in 2018 as Cube Analytics with a no code drag and drop analytics toolkit, Redbird added a conversational interface and then a specialist agent ecosystem on top. It is headquartered in New York, backed by B Capital, and works with eight of the Fortune 50 plus large government organizations, offering turnkey on premises deployments that run LLMs in the enterprise's own cloud so data is never used to train models for other customers.

Vendor details

Canonical URL

https://www.redbird.io

Subcategory

Conversational AI analytics

Funding status

Seed; B Capital backed; founded 2018 as Cube Analytics; customers include eight of the Fortune 50

Company status

independent

Use cases & customers

Primary use cases

Conversational business intelligenceAutomated data engineering and wranglingData science and forecastingAutomated PowerPoint and Excel reportingSelf serve analytics for non technical users

Target customers

Enterprise data and analytics teamsMarketing and operations teamsFortune 50 brands and government organizations

Deployment options

SaaSOn-prem (LLMs in customer cloud)

Integrations

Native integrations with databases, cloud storage, SaaS tools, and internal APIs; pulls structured and unstructured data from over one hundred sources including Snowflake, Databricks, and HubSpot; RPA and web scraping for third party data; outputs to PowerPoint, Excel, dashboards, email, and Slack; AWS Marketplace availability.

In practice

A marketing analyst asks a business question in plain language and Redbird's routing agent dispatches data engineering, data science, and reporting agents to return a finished analysis and deck in minutes

A domain expert loads data ontologies and business logic into the admin layer so agent answers stay accurate and governed across the organization

A security sensitive enterprise runs Redbird on premises with LLMs contained in its own cloud so proprietary data never trains external models

Sources & related URLs

Research sources

https://www.redbird.io/ https://www.redbird.io/post/conversational-ai-analytics-platform https://venturebeat.com/data-infrastructure/redbird-supercharges-analytics-pipeline-with-ai-agents-handles-90-of-workload https://docs.redbird.io/

Capability coverage

11.5 / 14 capabilities · 82%

Integrations & Tool CallingNative integrations with databases, cloud storage, SaaS tools, and internal APIs, pulling from over one hundred sources including Snowflake, Databricks, and HubSpot, plus RPA and web scraping for third party data, with no custom engineering required. redbird.io homepage and VentureBeat coverage retrieved 2026-07-08.	Full
Workflow OrchestrationA routing agent identifies the best specialist agents for a prompt and orchestrates their execution order across data collection, engineering, science, and reporting, with an orchestration engine connecting interconnected building blocks end to end. redbird.io conversational AI blog and VentureBeat retrieved 2026-07-08.	Full
Knowledge Grounding & RAGAn admin layer loads data ontologies, field definitions, business logic, and reporting blueprints so agents ground answers in the enterprise's own data and definitions, ensuring accuracy and governance. redbird.io conversational AI blog retrieved 2026-07-08.	Full
Human Oversight & GuardrailsAgents create a no code version of every workflow that users can audit and inspect, users can modify agent built steps via point and click or code, and data teams can override any AI generated admin configuration. redbird.io homepage and VentureBeat retrieved 2026-07-08.	Full
Security, Identity & GovernanceTurnkey on premises deployments run LLMs in contained environments on the enterprise's own cloud so data stays within the enterprise ecosystem and is never used to train models for other customers, with the admin layer providing governance control. redbird.io launch coverage (KMWorld, GlobeNewswire) retrieved 2026-07-08.	Full
Observability & AuditabilityEvery data pull, transformation, calculation, and output is logged and visible, and every step an AI agent takes is explained and inspectable so nothing is a black box. redbird.io homepage retrieved 2026-07-08.	Full
Memory & State PersistenceThe admin layer persists ontologies, business logic, and reporting blueprints that agents reuse across sessions, and workflows are saved and rerunnable; a dedicated agent memory construct is not separately documented. redbird.io conversational AI blog retrieved 2026-07-08.	Partial
Deployment & Data ResidencyOffers turnkey on premises deployments that run LLMs within contained environments on the enterprise's own cloud, alongside the SaaS offering and AWS Marketplace availability. redbird.io launch coverage and AWS Marketplace listing retrieved 2026-07-08.	Full
Prebuilt Agents, Templates & PacksShips an ecosystem of specialized prebuilt agents (Data Engineering, Data Science, PowerPoint Reporting, routing) plus reusable reporting blueprints and no code building blocks across the analytics lifecycle. VentureBeat and redbird.io conversational AI blog retrieved 2026-07-08.	Full
Triggers & Channel CoverageWorkflows can automate data collection on a chosen cadence and take actions like triggering alerts, populating CRMs, and sending Slack or email updates, but broad event trigger and channel configuration is not detailed. redbird.io homepage retrieved 2026-07-08.	Partial
Model Flexibility & RoutingOn premises deployments can run LLMs in the enterprise's own cloud, implying model flexibility, and a proprietary domain specific language handles analytics tasks LLMs struggle with; explicit customer model selection or routing is not detailed. redbird.io conversational AI blog and launch coverage retrieved 2026-07-08.	Partial
APIs, SDKs & MCP ExtensibilityDocumentation publishes an llms.txt index and OpenAPI endpoints and the platform connects to internal APIs, indicating a developer surface, but a fully documented public API, SDK, or MCP interface for building on the platform is not detailed. docs.redbird.io retrieved 2026-07-08.	Partial
Testing, Debugging & OptimizationSelf healing agents automatically detect and fix steps that break when data, APIs, or interfaces change, and the no code inspectable workflow lets users audit and correct agent output before reruns. redbird.io homepage retrieved 2026-07-08.	Full
Browser & Computer UseData collection includes RPA and web scraping for third party data, which involves browser based extraction, but a general computer use agent is not the framing. redbird.io conversational AI blog retrieved 2026-07-08.	Partial

Recent platform changes

No recent material changes tracked yet.

View all changes for Redbird →

Pricing

Contact sales

Contact onlyMedium variable cost

What is public

Product capabilities, on premises deployment option, and AWS Marketplace availability are public; commercial terms are not.

Billing mechanics

Not publicly documented; sales led with a demo funnel and AWS Marketplace availability.

Cost watchouts

On premises deployments running LLMs in the customer's cloud add infrastructure and compute cost; pricing likely scales by users, data sources, or workflow volume.

Variable cost rationale

Analytics platforms of this type typically price by users, data sources, or workflow runs, which scales with adoption, and on prem LLM deployments add compute cost; no metering is published, so exposure is inferred.

Additional watchouts

Enterprise analytics procurement; on prem LLM deployments carry additional infrastructure cost.

Sales call required

Yes — required for paid access

Free / trial

Demo request; no public free tier or self serve trial documented

Key ambiguities

Pricing axis and figures are unpublished; AWS Marketplace listing exists but public rates were not retrieved.

Missing data

All pricing figures, billing axis, trial terms.

Verified 2026-07-08

Official pricing page

Data confidence: high