Prophet
Also known as: Prophet AI, Prophet.ml
Decision intelligence platform that builds a living digital clone of your business and answers natural language questions by running fresh simulations to test decisions before you act.
Prophet is a decision intelligence platform that goes beyond traditional marketing mix modelling by building a living digital clone, a detailed mathematical model, of each organization spanning marketing, pricing, operations, supply chain, and external market conditions, continuously updated with around 86,000 macroeconomic data points for near real time context. Rather than reading past dashboards, Prophet lets teams simulate what could happen and test decisions before releasing them into the real world, controlling every factor that affects business performance in minutes. Its Prophet AI agent, launched in late 2025, makes this accessible through conversational queries: every question triggers fresh computation, running new simulations against the digital clone to explain what is driving performance and where the opportunities lie, and users can issue agentic commands to control the Prophet ecosystem, with the agent notifying them when results are ready. The Prophet Library adds an ever growing repository of economic, socio economic, behavioural, and market data to build rigorous baselines, an Analytics+ module makes outputs and data fully customizable to an organization's language and KPIs, and a Secure AI environment handles sensitive organizational data. Roadmap features include automated scenario generation, shock testing, and proactive insight discovery to surface opportunities and risks before they appear in the data.
Vendor details
Canonical URL
https://www.prophet.ml
Category
Data analyst agent
Funding status
Based in Melbourne and Sydney, Australia; launched in 2024. Reports more than 30 enterprise clients across retail, insurance, automotive, media, on-demand delivery, wagering, and cybersecurity. CEO Jordan Taylor-Bartels; advisory board includes Phil Davis (former VP Global GTM at Google Cloud) and Professor Andrew Gelman of Columbia University. Specific funding figures were not retrieved this session.
Company status
independent
Use cases & customers
Primary use cases
Target customers
Deployment options
Integrations
Integrates data pipelines, media platforms, and the broader tech stack at scale via APIs, CSVs, and natural language, with typical onboarding of 6 to 8 weeks. Continuously ingests roughly 86,000 macroeconomic data points to contextualize performance.
Sources & related URLs
Research sources
Capability coverage
8.0 / 14 capabilities · 57%
| Integrations & Tool CallingIntegrates data pipelines, media platforms, and the broader tech stack at scale through APIs, CSVs, and natural language, and continuously ingests roughly 86,000 macroeconomic data points, with a 6 to 8 week onboarding. | Full |
|---|---|
| Workflow OrchestrationProphet AI runs fresh simulations against the digital clone on every query and lets users issue agentic commands to control the Prophet ecosystem, orchestrating multi factor scenario computation rather than reading static outputs. | Full |
| Knowledge Grounding & RAGAnswers are grounded in a living mathematical digital clone of the organization plus the Prophet Library of economic, behavioural, and market data and about 86,000 macro data points; the agent computes results afresh rather than guessing from past outputs. | Full |
| Human Oversight & GuardrailsProphet is decision support: teams simulate and test decisions before releasing them into the real world and make the final call, but no formal approval or guardrail construct over the agent's actions is documented. | Partial |
| Security, Identity & GovernanceProvides a Secure AI environment for handling sensitive organizational data and addresses data security explicitly, but specific security or compliance certifications were not retrieved this session. | Partial |
| Observability & AuditabilityThe agent lets users diagnose drivers and explains what is influencing performance across functions, providing transparency into results, but no dedicated agent action audit log is documented. | Partial |
| Memory & State PersistenceThe living digital clone is a persistent, continuously updated mathematical model of the organization that reflects both historic and predicted behaviour and is remodelled daily, providing strong persistent state that the agent reasons over. | Full |
| Deployment & Data ResidencyDelivered as a customizable cloud SaaS platform with a secure environment. No on premise or configurable data residency options are documented on the retrieved pages. | Partial |
| Prebuilt Agents / Templates / PacksOffers prebuilt modules including Analytics+ for customizable outputs, the Prophet Library data repository, and a Secure AI module, but not a broad user composable catalog of agents or templates. | Partial |
| Triggers & Channel CoverageProvides daily near real time remodeling and query triggered simulations, notifying users when results are ready, while proactive insight discovery and shock testing are described as roadmap features rather than shipped triggers. | Partial |
| Model Flexibility & RoutingProphet runs its own proprietary mathematics and neural networks. No customer selectable model or multi provider routing is documented on the retrieved pages. | Unable to verify |
| APIs / SDKs / MCP ExtensibilityIntegrates via APIs and exposes a customizable Analytics+ module for amending modelled outputs and data, but no public SDK or MCP surface for building on Prophet is documented. | Partial |
| Testing, Debugging & OptimizationSupports scenario testing, baseline computation (what would happen without marketing), and statistically justified models, with shock testing on the roadmap, providing model validation though not a general agent evaluation harness. | Partial |
| Browser / Computer-useProphet operates over data, models, and simulations. No browser automation or general computer use capability is documented. | Unable to verify |
Pricing
Contact sales; no public pricing. Enterprise decision intelligence platform with 6 to 8 week onboarding.
not disclosed; enterprise platform
Cost watchouts
Onboarding involves data integration and model calibration over several weeks. Cost is scoped per enterprise deployment and data scale rather than a public rate.
Variable cost rationale
Enterprise platform scoped by data scale and deployment; no public rate card, so exposure is moderate and not precisely determinable.
Sales call required
Yes — required for paid access
Free / trial
No public free tier; enterprise engagement
Lowest paid plan
Not public
Key ambiguities
No public pricing. Whether billing is per seat, per model, or platform tier is not disclosed.
Related vendors
- AskYourDatabase — AskYourDatabase is a conversational data analyst that turns plain…
- Athenic AI — Athenic AI is an agentic data analyst that connects business apps…
- BlazeSQL — BlazeSQL is an AI data analyst that learns your SQL database, turns…
- Brewit — Brewit is a conversational business intelligence agent that turns…
- Buster — Buster is an open source, artificial intelligence native data…
- camelAI — AI data analyst turned AI software engineer that chats with your…