Overview

Users choose an outcome and forecast horizon; Predict.ai searches for drivers, backtests competing models on historical data, and reevaluates deployed forecasts as data changes. That ongoing loop suits businesses whose assumptions and inputs move over time better than a forecast that is produced once and left alone. Forecast dimensions include product, region, bookings, pipeline, usage, renewals, pricing, and seasonality, including financial forecasting.

Scenario planning compares a baseline with a forecast after a user changes a driver or schedules an event. It is useful for exploring possibilities, not evidence that the changed factor caused the result; decisions that require causal proof need more than this comparison.

Key features

Data connections and analytics: Inputs include file uploads, REST, Kafka, S3, BigQuery, PostgreSQL, and webhooks. Trends, anomalies, recurring rhythms, correlations, lead-lag relationships, and leading indicators help users examine connected signals before relying on them for forecasts.
Model comparison and serving: Multiple models are backtested on historical data, then forecasts can be delivered through hosted REST endpoints, streaming, or batch inference. Quantile bands add a view of forecast ranges, useful when a single estimate would conceal uncertainty.
Developer interfaces: A REST API, Python and TypeScript SDKs, WebSockets, and MCP support for AI agents give technical teams several ways to integrate forecasts. The API and self-hosted platform options make it more suitable for implementation-led buyers than for someone seeking only a standalone planning interface.
Data protections: Predict.ai says workspace data is isolated and not used to train shared or other customers' models. It states that data in transit uses TLS 1.2 or higher and customer content and backups are encrypted at rest using AES-256 or equivalent. EU-region workspace content stays in the EU unless the customer instructs otherwise, which matters to organizations with regional data requirements.

Pricing

The Free plan costs 0.00 USD per free, billed forever. It includes 500 credits per month, described as $5 of usage, one workspace, one seat, one goal per workspace, one shared deployment, and 1 GB of ingestion per month. The hard monthly credit cap makes it a constrained way to explore the product, not a flexible free production tier.

Starter costs 149.00 USD per month, billed per month. It raises the allowance to 5,000 credits ($50 of usage), two workspaces, one seat, 10 goals per workspace, three shared deployments, and 20 GB of monthly ingestion. It is aimed at solo builders shipping to production; usage above included credits costs $0.01 per credit. The single seat is a real constraint for collaboration.

Team costs 2499.00 USD per month, billed per month. It includes 50,000 credits ($500 of usage), five workspaces, five seats, 50 goals per workspace, 10 shared and two dedicated deployments, and 100 GB of monthly ingestion. Additional seats cost $99/seat after the five included. The larger allowance and dedicated deployments suit teams shipping forecasts together, but the price step from Starter is substantial. Above included credits, usage is $0.01 per credit.

Enterprise has custom pricing on an annual contract, with a custom credit allowance, 25 workspaces, 200 goals per workspace, 50 shared and five dedicated deployments, and 1,000 GB of monthly ingestion. SSO / SAML and on-premises deployment distinguish it for mission-critical, regulated, or very large workloads; an annual commitment makes it a less natural fit for buyers seeking a short-term commitment.

Platforms

Predict.ai is offered on web, through an API, and as self-hosted software. This spread supports both direct workspace use and integration into existing systems, though buyers should choose based on how they intend to serve forecasts rather than assuming every interface is interchangeable.

Who it's for

Predict.ai is best suited to technically capable solo builders and teams that need repeatable, updating forecasts and want to compare models, inspect connected signals, or serve results into other systems. Its scenario comparisons can help finance and revenue teams explore changes across the supported forecast dimensions. It is a weaker match for a one-seat buyer whose needs exceed Starter's allowance, a team that cannot justify the Team price, or anyone treating scenario comparisons as proof of cause and effect.

Pros and cons

Pros: A workflow from driver discovery through backtesting and reevaluation reduces the gap between analysis and an operating forecast.
Pros: Broad listed data inputs and REST, streaming, and batch serving give implementation teams flexibility.
Pros: Workspace isolation, encryption claims, and EU-region storage commitments address meaningful data-handling concerns.
Cons: Free is capped at 500 credits per month, and paid overages are metered at $0.01 per credit, so usage needs monitoring.
Cons: Starter has one seat, while Team begins at 2499.00 USD per month; collaboration can therefore require a large spend increase.
Cons: Scenario comparisons do not establish causation, limiting their value for decisions that depend on causal attribution.

Alternatives

Choose Revenue Planning Software if you want to compare options across that category, or Cash Forecasting Software for a category-focused shortlist. Augmented Analytics Software and Revenue Intelligence Software are also broader category starting points.

Salesforce Sales Cloud is worth considering when a freemium option with a free plan and free trial, plus a $25.00-per-month Starter Suite, fits better than a forecasting-specific platform.
ModusCPG Scout is a web-based paid alternative with pricing not published and a demo booking route.
Pyplan Quota Planning is an option when API, self-hosted, and web platforms matter; its Starter and Teams prices are not published.
Workday Adaptive Planning offers a 30-day free trial and broad platform coverage, but has no free plan and its paid pricing varies.
Apliqo FPM is a paid web and self-hosted alternative with pricing available from sales on request.
Jedox has paid Business and Professional plans, with pricing not published.
Planful is an API and web alternative with subscription pricing tailored to company size, user count, and selected modules.
Fintastic is a paid web-based alternative.

Verdict

Choose Predict.ai if you need forecasts that can be backtested, deployed, and revisited as business data changes, and have the technical capacity and budget to operate them. Its clearest advantage is the connected path from signals to serving; the main reasons to look elsewhere are the limited free cap, Starter's solo seat, the costly Team step, and the fact that scenario comparisons are not causal proof.

	Muntri	Predict.ai
Free plan	Yes	Yes
Free trial	Yes	No
Paid from	$299/mo	$149/mo
Open source	No	No
Platforms	api, iOS, Web	api, self-hosted, Web
Free plan	No	Yes
Deal risk alerts	Yes	—
AI forecasting	Yes	—
Recommended actions	Yes	—
Connected data sources	multi_source	—

Muntri vs Predict.ai

Muntri

Predict.ai