Predict.ai

Predict.ai is a forecasting platform for businesses that want to identify drivers, compare models, and keep forecasts updated as inputs change. It is strongest for builders and teams deploying forecasts through software interfaces. Its flexible data and serving options are balanced by a strict free-tier ceiling and a substantial jump to the Team plan.

Overview

Choose a business outcome and forecast horizon, and Predict.ai searches for useful drivers, tests multiple models against historical data, and can deploy a forecast that is reevaluated as new data arrives. This continuous workflow is more suitable for changing operations than a forecast produced once and left untouched. Supported dimensions include product, region, bookings, pipeline, usage, renewals, pricing, and seasonality, including financial forecasting.

Scenario planning lets users adjust a driver or schedule an event, then compare the resulting forecast with a baseline. That is useful for weighing possible outcomes, but it does not establish that the changed factor caused them.

Key features

• Connected data and signal analysis: Inputs include file uploads, REST, Kafka, S3, BigQuery, PostgreSQL, and webhooks. The workspace can surface trends, anomalies, recurring rhythms, correlations, lead-lag relationships, and leading indicators. This breadth helps teams examine several kinds of business signals, though the value depends on having relevant data to connect.
• Model selection and deployment: Predict.ai backtests multiple models on historical data, then serves forecasts through hosted REST endpoints, streaming, or batch inference. Responses include quantile bands, giving consumers a range around forecasts rather than only a single value.
• Developer access: A REST API, Python and TypeScript SDKs, WebSockets, and MCP support for AI agents give engineering teams several ways to integrate forecasts. This is a practical advantage for software-driven workflows, but less compelling for buyers who do not need programmatic access.
• Data protection: Predict.ai says workspace data is isolated and is not used to train shared models or models for other customers. Data in transit uses TLS 1.2 or higher, and customer content and backups are encrypted at rest with AES-256 or equivalent. Each workspace has a home region; EU workspace content stays within the EU unless the customer instructs otherwise.

Pricing

Predict.ai uses a freemium model. The plans differ not only in monthly credits, but also in seats, workspaces, goals, deployments, and ingestion, so the lowest monthly price is not the whole cost or capacity picture.

Plan	Price and terms	Included capacity
Free	free; billed forever	500 credits per month ($5 of usage), 1 workspace, 1 seat, 1 goal per workspace, 1 shared deployment, and 1 GB ingestion per month
Starter	$149 a month; billed per month	5,000 credits per month ($50 of usage), 2 workspaces, 1 seat, 10 goals per workspace, 3 shared deployments, and 20 GB ingestion per month
Team	$2,499 a month; billed per month	50,000 credits per month ($500 of usage), 5 workspaces, 5 seats included, $99/seat after, 50 goals per workspace, 10 shared and 2 dedicated deployments, and 100 GB ingestion per month
Enterprise	Custom pricing; billed annual contract	Custom credit allowance, 25 workspaces, 200 goals per workspace, 50 shared and 5 dedicated deployments, 1,000 GB ingestion per month, SSO / SAML, and on-premises

Free is a useful way to evaluate a small workflow, but 500 credits per month are a hard cap, and one seat, one goal, and one shared deployment restrict it to a narrow setup. Starter raises the allowance and ingestion ceiling and is positioned for solo builders shipping into production; it remains a one-seat plan. Usage above included credits costs $0.01 per credit on both Starter and Team, so sustained usage beyond the allowance adds to the monthly bill.

Team is designed for teams shipping forecasts together, with five seats included and shared as well as dedicated deployments. At $2,499 a month, it is a large step up from Starter; the extra seats, goals, and capacity matter only if the workload needs them. Additional seats cost $99/seat after the five included. Enterprise uses custom pricing under an annual contract and adds SSO / SAML and on-premises deployment, making it the plan aimed at mission-critical, regulated, or very large workloads rather than buyers seeking a published monthly rate.

Platforms

Predict.ai is available as a web product, API, and self-hosted option. The API and SDK choices suit teams embedding forecast outputs into applications or agent workflows; self-hosting and regional storage options may matter to organizations with deployment or data-location requirements.

Who it's for

Predict.ai is a good fit for solo builders moving forecasting into production and for teams that need to compare models, revisit assumptions, and deliver forecasts to other systems. Its scenario comparisons and broad business dimensions also suit financial and operational planning. It is a weaker fit for individual users who need more than one seat on a modest budget, or anyone whose work depends on proving causality rather than comparing forecast scenarios.

Pros and cons

• Pro: It joins driver discovery, historical model comparison, deployment, and reevaluation in one forecasting workflow, which is useful when inputs keep changing.
• Pro: Multiple data connectors, inference modes, SDKs, and API interfaces give technical teams several integration paths.
• Pro: Quantile bands, workspace isolation, encryption, and EU-region storage terms address forecast uncertainty and data-handling needs.
• Con: The free plan is capped at 500 credits monthly and limited to one seat, one goal, and one shared deployment, so it is not a roomy ongoing tier.
• Con: Starter permits only one seat, while Team costs $2,499 a month before any overage credits or additional seats, making collaboration expensive for smaller teams.
• Con: Scenario comparisons do not prove causation, so they cannot substitute for causal evidence when that is the decision requirement.

Alternatives

For a bank-connected cash forecast and a simpler small-team starting point, consider Dibein: its free Starter plan includes one bank connection, one accounting connection, a rolling 13-week forecast, up to two seats, and seven-day Anomaly Radar history. Pick Cashflow CaFE instead if you want a paid cash-flow app across Android, iOS, and web; it offers a free trial.

Kyriba is another paid option, with a custom-priced Treasury plan and Android, iOS, API, and web platforms. Consider Agicap if you want a paid cash-management alternative with a free trial, while accounting for its minimum 12-month subscription. Awesome Forecast is worth considering for a Windows user seeking a single-license annual plan, priced at £250 a year, with a free plan and trial.

If you want a web-based forecasting option with a free trial and unlimited users on its Premier1 plan, compare Calxa, which starts at $18 a month for one organisation. CashAnalytics is a paid web alternative with pricing on request. Nomentia Cash Flow Forecasting is another paid web option.

For category browsing, see Cash Forecasting Software, Revenue Planning Software, Augmented Analytics Software, and Revenue Intelligence Software.

Verdict

Choose Predict.ai if you need driver-focused forecasts that can be compared, served, and refreshed through production interfaces. Its strongest case is the combination of model comparison, scenario work, and integration breadth. Look elsewhere if the 500-credit free cap is too restrictive, you need multiple seats without paying for Team, or the 2499.00 USD monthly Team price does not fit the workload.