Foundry vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-10-30
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Foundry or Temporal AI: which should you choose?

DimensionFoundryTemporal AI
PricingContact for pricingFree (open-source, self-hosted) + Cloud freemium/usage-based billing
Best forBuilding, evaluating, and training browser-based AI agentsDurable orchestration for AI agents, microservices, and long-running workflows
Core strengthPixel-perfect, reproducible browser simulation for agent trainingFault-tolerant execution with automatic state capture and retries
SDK/IntegrationPython SDK, integrations with Gmail, Sheets, Salesforce, LinkedInMultiple SDKs (Python, Go, TS, Java, etc.) + AI agent integrations (OpenAI, Google ADK)
Target usersAI researchers and teams building browser automation agentsDevelopers building reliable distributed systems and AI workflows
Latency profileSimulation and evaluation, not real-time inferenceDesigned for durable, long-running workflows (not low-latency sync)

Choose Temporal AI if you need a battle-tested durable execution platform for orchestrating any multi-step process—AI agents, microservices, or human-in-the-loop workflows—with automatic retries and state management. Choose Foundry if your primary need is a high-fidelity browser simulation environment for training and evaluating web agents. They serve different layers: Temporal for orchestration reliability, Foundry for agent training data and evaluation.

Foundry
Foundry

Reproducible browser environments, evaluation, and training data for teams building AI web agents.

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Contact Sales
Paid
Plans
—
FreeFree trial
Pay-As-You-GoFrom $50/1M actions
Business Support Add-On$500/mo
Enterprise and Mission CriticalCustom
Popularity
4 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
WebAPI
WebAPI
Categories
🖱️ Browser & Computer-Use Agents🧪 Software Testing & QA
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
Pixel-perfect reproducible browser environments for agent simulation
Resettable environment state between evaluation runs
No drift, noise, or rate limits across runs
Per-action tracking, classification, and tagging of agent behavior
Click failure, layout shift, and misfire detection
Event recording with append-only state mutation history
Ground-truth comparison via heuristic scoring
Python SDK that plugs into existing agent workflows
CDP URL retrieval to control and observe browser agents
Task structure carrying login credentials and payment details
Expert-annotated long-horizon datasets for supervised fine-tuning
Datasets built on real enterprise platforms
Unlimited trajectory sampling and evaluation for RL
RL gym without anti-bot constraints
SDRBench benchmark and RL gym with 50 deterministic enterprise SaaS tasks
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Serverless Workers for Google Cloud Run, public preview (2026-10-05)
Serverless Workers for AWS Bedrock AgentCore, pre-release (2026-09-18)
Native Task Queue priority and fair distribution without a custom queueing layer
Durable Timers that sleep for months; cron Schedules with backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to a version so deploys don't corrupt in-flight runs
Cloud UI Strict Session Mode: 15-minute inactivity timeout, 12-hour max session (GA)
Replay tests validate against real histories; time-skipping tests fast-forward long timers in CI
Integrations
Gmail
Google Sheets
Salesforce
Apollo
OpenAI Agents SDK
Google ADK
AWS Lambda
Google Cloud Run
Amazon Bedrock AgentCore
Kubernetes
GitHub Actions
GCP Marketplace
Azure
Slack

Who should pick Foundry, and who should pick Temporal AI?

  • AI agent developer building reliable multi-step workflows
    Pick: Temporal AI

    Temporal’s durable execution ensures agent workflows survive failures and can pause for human input, with automatic retries and state recovery.

  • Researcher training browser-based web agents
    Pick: Foundry

    Foundry provides pixel-perfect simulation, evaluation metrics, and SDRBench for RL training, essential for building robust browser agents.

  • Enterprise orchestrating microservices with Saga patterns
    Pick: Temporal AI

    Temporal natively supports Saga compensating transactions and provides visibility into each step, ideal for financial or order processing systems.

  • Sales team automating CRM workflows with browser agents
    Pick: Foundry

    Foundry integrates with Salesforce and LinkedIn, and its simulation environment is tailored for enterprise SaaS workflows like prospecting and data entry.

  • Startup building AI agents with minimal infrastructure overhead
    Pick: Temporal AI

    Temporal’s open-source self-hosted option and freemium Cloud tier allow startups to start free and scale with usage-based billing.

Frequently Asked Questions

Foundry vs Temporal AI: which should you choose?

Choose Temporal AI if you need a battle-tested durable execution platform for orchestrating any multi-step process—AI agents, microservices, or human-in-the-loop workflows—with automatic retries and state management. Choose Foundry if your primary need is a high-fidelity browser simulation environment for training and evaluating web agents. They serve different layers: Temporal for orchestration reliability, Foundry for agent training data and evaluation.

Can Temporal be used for browser agent orchestration?

Yes, Temporal can orchestrate browser agent workflows by coordinating steps, handling retries, and managing human-in-the-loop signals. However, it does not provide browser simulation; that's Foundry's domain.

Does Foundry offer durable execution?

No, Foundry is focused on simulation and evaluation, not on ensuring workflow durability across crashes. Temporal is the right choice for that.

Which tool is better for training AI agents?

Foundry is specifically designed for training browser agents with simulation and RL. Temporal can orchestrate the training pipeline but doesn't simulate browser environments.

Can I use Temporal for free?

Yes, Temporal's core is open-source and you can self-host it for free. Temporal Cloud offers a free tier with usage-based billing.

Is Foundry open-source?

No, Foundry is a commercial product with contact-based pricing. There is no self-hosted or open-source version.

Which integrates with OpenAI Agents SDK?

Temporal AI recently announced integration with OpenAI Agents SDK (Replay 2026). Foundry does not list such integration.

Can Foundry handle long-running workflows with human approval?

Foundry is for simulation and training, not for running production workflows. Temporal's human-in-the-loop signals and pause/resume are designed for that.

What is the latest news about Foundry?

Foundry released SDRBench on September 22, 2025, a benchmark and RL gym for browser agents with 50 tasks across enterprise SaaS.

What else are Foundry and Temporal AI compared with?

Where can you read more about Foundry and Temporal AI?

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