Context
Enterprise agent execution for governed workflows, scoped access, reusable knowledge, and ongoing quality checks.
About Context
Context is an enterprise platform for building, deploying, and improving AI agents across real workflows. Workspace lets teams write runbooks in plain English and work beside agents with a full audit trail. Engine provides scoped identity, tools, compute, a separate sandbox for each session, and more than 800 permissioned connectors. It can run as a hosted service, in a customer VPC, on premises, or in an air-gapped environment. Unify carries procedures, earlier work, permissions, and expert corrections into later runs. Evals scores results against rubrics written by domain experts and can send familiar work to the lowest-cost model that still meets the required standard. Context fits organizations that need agents to act across several systems while keeping human approval and governance in place. Rolling it out means connecting identity, permissions, data sources, runbooks, and evaluation criteria. This is an enterprise platform implementation, not a lightweight personal assistant. Pricing requires a sales conversation, which makes quick cost comparisons and self-service evaluation difficult.
Best for
Best use cases
A team turns a recurring multi-system process into a plain-English runbook and approves sensitive agent actions.
An organization runs agents inside its perimeter while inheriting each user's identity and tool permissions.
Domain experts score completed work with rubrics and test workflow or model changes against accepted examples.
Compare before choosing
Choose Context over a single-app copilot when work must continue across tools and leave a durable execution trace.
Choose Context over a vertical AI interface when several departments need one governed agent execution system.
Consider a simpler assistant when the workflow stays in one app and does not require private deployment or formal evaluations.
Features
Cross-system workflow execution
Define runbooks in plain English so agents can complete governed work across several enterprise systems with human steering and approval.
Permission-aware knowledge reuse
Carry procedures, prior work, and expert corrections into future runs while respecting the grants of the person invoking the agent.
Continuous agent evaluation
Score every run against expert-authored rubrics, test changes against accepted work, and route known tasks to a lower-cost model that still passes.
Pros
- More than 800 permissioned connectors reduce the custom integration work needed for cross-system agent workflows.
- Hosted, VPC, on-premises, and air-gapped options support organizations with different infrastructure and data-boundary needs.
- Per-run scoring, audit trails, scoped identity, and approval controls make agent behavior easier to govern and review.
Cons
- Sales-led pricing makes early budget comparison harder because there is no public list price or billing interval.
- Connecting identity, permissions, data sources, runbooks, and rubrics creates a substantial implementation workload.
- The broad enterprise platform may be excessive for teams that only need assistance inside one application or a narrow workflow.
Pricing Plans
Enterprise
- Workspace for plain-English runbooks and audited collaboration
- Engine runtime with scoped identity, sandboxes, and 800+ connectors
- Unify context layer for procedures, prior work, and corrections
- Evals with expert-authored rubrics and model routing
* Pricing information is for reference only. Please refer to the latest announcement on Context's official website.