Parallel is an AI infrastructure platform designed to help organizations deploy and run large numbers of AI agents simultaneously on complex, multi-step tasks. It provides the underlying compute and orchestration layer that handles the coordination challenges of running agents in parallel — scheduling, resource allocation, and task distribution — so engineering teams can focus on building agent logic rather than managing infrastructure. The platform targets enterprise teams that need to move beyond single-agent prototypes into production-scale deployments. It differentiates itself by focusing specifically on the infrastructure layer rather than agent frameworks or applications, positioning as a foundational piece of an enterprise’s agentic stack.
Parallel
Compute and orchestration for large-scale AI agents.
Compliance
SOC 2
Key Features
- Parallel agent execution: Run many agents concurrently on a single complex task, enabling workflows that would be too slow or impractical with sequential processing.
- Orchestration layer: Manages task distribution, sequencing, and dependencies across agents without requiring teams to build custom coordination logic.
- Compute management: Abstracts the underlying infrastructure so teams don’t need to manually provision or scale resources as agent workloads grow.
- Multi-model support: Works across multiple LLM providers, giving teams flexibility in which models power their agents.
- Enterprise-grade reliability: Built with production deployments in mind, including SOC 2 compliance and the operational guarantees enterprise buyers require.
Use Cases
- For enterprise engineering teams scaling agentic workflows: A team that has built a working prototype of an agent pipeline needs to run it across thousands of documents or data sources simultaneously — Parallel provides the infrastructure to do this without building a custom orchestration system from scratch.
- For AI platform teams managing complex multi-agent systems: An internal AI platform team needs to coordinate multiple specialized agents (research, summarization, action-taking) working in concert on a single task, and relies on Parallel to handle the scheduling and execution layer.
Pricing MODELS
Enterprise
Pricing Summary
Parallel uses a custom enterprise pricing model — no self-serve or publicly listed tiers are available. Interested buyers need to contact the company directly for a quote.
Company Size Fit
Enterprise
Technical Snapshot
API Available
Yes
LLM Provider
Multi-model
Open Source
No
Deployment Options
Cloud Saas