Beam

Ingests unstructured process documentation (SOPs, workflow descriptions, text-based procedures) and automatically generates executable AI agents capable of performing multi-step tasks without manual coding. The system parses natural language process descriptions, extracts task sequences and decision logic, and compiles them into agent behavior specifications that can be deployed to production. This eliminates the need for developers to manually code workflow logic.

Executes complex, multi-step workflows where agents perform sequential or branching tasks across multiple external systems, with built-in output evaluation and self-healing mechanisms. The system orchestrates task execution, validates outputs against expected results, and automatically retries or corrects failed steps without human intervention. Supports unlimited workflow steps on Pro+ plans, enabling agents to handle complex business processes with dozens of sequential operations.

Collects detailed execution data from every agent task including inputs, outputs, success/failure status, latency, and outcomes. This data is used for analytics, reporting, and feeding the self-learning system. The system provides visibility into agent performance and enables data-driven optimization of workflows.

Provides dedicated solution engineer support on Custom plans to assist with custom integrations, enterprise deployment, and complex workflow configuration. This is a human-in-the-loop service for high-value customers, suggesting that custom integrations and enterprise deployments require significant professional services.

Agents automatically improve their performance over time by analyzing execution data, identifying patterns in successful vs. failed tasks, and updating their behavior without manual retraining. The system collects data from every agent execution, extracts learnings about what works and what doesn't, and applies those learnings to future task execution. This is available only on Scale and Custom plans, suggesting it requires significant computational resources.

Provides ready-to-deploy, pre-configured agents for common Finance and HR workflows including invoice reconciliation, accounts receivable management, financial compliance reporting, and debt collection. These agents are pre-trained on domain-specific patterns and integrate with standard accounting and HR systems. Users can deploy these agents with minimal configuration, avoiding the need to build agents from scratch for common use cases.

Executes agent tasks with pricing and rate limits tied to monthly task volume. The system tracks task execution, enforces monthly quotas (20 tasks/month on Free, 200 on Pro, undefined on Scale), and meters access based on plan tier. Tasks are the atomic unit of billing and execution; each agent action counts as one task. This enables usage-based pricing while preventing runaway costs.

Connects agents to external business systems (ERP, CRM, accounting software, HR systems) through pre-built or custom integration connectors. The system manages authentication, data transformation, and API orchestration between agents and target systems. Free/Pro plans include 1 base integration; Scale includes 3; Custom plans support unlimited integrations. Specific supported systems are not disclosed.

Provides security and compliance features for enterprise deployments including data encryption, audit logging, and compliance certifications (specifics undisclosed). These features are only available on Scale ($3,990/month) and Custom plans, suggesting they require additional infrastructure and operational overhead. Free and Pro plans do not include enterprise security features.

Offers tiered access to different AI models: 'Premium AI Models' on Pro plan and 'Frontier AI Models' on Scale plan. The specific models, versions, and providers are not disclosed. This suggests Beam either uses proprietary models, fine-tuned versions of third-party models, or has negotiated exclusive access to frontier models. The model tier directly impacts agent capability and accuracy.

Executes agent tasks in batches with monthly quota tracking and enforcement. The system accumulates task executions throughout the month, tracks usage against the plan's monthly quota, and prevents execution once the quota is exhausted. This enables predictable billing and prevents runaway costs but creates hard limits on monthly automation capacity.

Deploys configured agents to production environments and manages their lifecycle including versioning, updates, and rollback. Once an agent is deployed, it can execute tasks autonomously 24/7 without human intervention. The system handles agent monitoring, execution logging, and presumably error handling, though specific lifecycle management features are not documented.