What is Credal.ai?
Credal.ai is an enterprise platform for creating and governing MCP servers and AI agents. Credal.ai brings business tools, data, instructions, and reusable skills into a shared governance layer for platform teams and domain experts. The service focuses on giving agents selected context while maintaining access controls and visibility into model spending.
Credal.ai serves enterprises and scaling startups that want AI to operate within existing business systems. Teams can query connected resources through Claude, ChatGPT, Cursor, or their own applications. Shared rules and permissions follow tool calls across interfaces rather than requiring each team to recreate governance separately.
What Credal.ai can do
Credal.ai combines context curation, agent management, and cost oversight. Domain experts can select the tools and instructions a workflow needs, while platform teams maintain a registry of deployed agents and servers. Audit information supports both governance reviews and decisions about model spending.
- Credal.ai connects sources including Google Drive, Slack, Confluence, Salesforce, Jira, and Zendesk.
- Credal.ai scopes tools and enforces parameters that limit data access and actions.
- Credal.ai versions agents and MCP servers and supports rollback.
- Credal.ai attributes model costs to teams, workflows, and models.
- Credal.ai recommends cheaper models where accuracy holds.
- Credal.ai supports approval requirements for sensitive actions.
How Credal.ai works
Credal.ai connects existing data sources and automatically inherits their permissions. Domain experts then bundle relevant tools, data, and instructions into focused MCP servers. Access is enforced at query time, so a user without access to a source document does not gain access through an agent.
Credal.ai publishes governed capabilities across chat interfaces and custom applications, with a typed API for larger automation chains. Teams can use managed model access, connect an Azure OpenAI deployment, or bring self-hosted open-source models. Deployment options include multi-tenant cloud, single-tenant cloud, and fully on-premises installations.
Who Credal.ai is for
Credal.ai is designed for platform teams overseeing enterprise AI and domain experts who understand departmental workflows. Sales, revenue operations, support, and engineering teams can use shared agents and skills in their existing interfaces. The registry provides a common record of deployments, ownership, access rights, and changes.
- Credal.ai supports revenue operations workflows using Salesforce and warehouse data.
- Credal.ai supports customer support workflows using Zendesk and Confluence.
- Credal.ai shares reusable skills across Slack, Cursor, and Claude.
- Credal.ai helps platform teams audit agent actions and model spending.
Credal.ai pricing and plans
Credal.ai offers custom enterprise pricing scoped around teams, connected data, and usage. Pricing components include builder seats for agent and server creators, user seats for people using deployed agents, data indexing, and usage-based model tokens. Prospective customers contact sales to define a plan.
Credal.ai includes SSO, SAML, SCIM, consolidated audit logs, SIEM export, and a dedicated support channel in every plan. The pricing page also describes time-boxed pilots focused on a team or use case, with success criteria defined upfront and support from an onboarding team.
Credal.ai strengths and limitations
Credal.ai brings source permissions, shared instructions, agent versioning, and spending oversight into a common gateway and registry. Model-agnostic operation and multiple deployment options support different infrastructure requirements. Security provisions include SOC 2 Type II certification, full audit logging, and support for HIPAA-compliant configurations.
- Credal.ai requires contacting sales for a scoped enterprise quote.
- Credal.ai charges for model token consumption as a pricing component.
- Credal.ai implementation scope affects enterprise rollout timing.
Credal.ai FAQ
What is Credal.ai?
Credal.ai is an enterprise platform for building and governing MCP servers and AI agents. Credal.ai connects business sources, curates agent context, enforces access permissions, and provides a shared registry with auditing and model cost visibility.
How much does Credal.ai cost?
Credal.ai uses custom enterprise pricing based on builder seats, user seats, data indexing, and model token usage. Credal.ai asks prospective customers to contact sales to scope a plan around their teams, connected data, and intended usage.
Which tools and models does Credal.ai support?
Credal.ai connects sources including Google Drive, Slack, Confluence, Salesforce, Jira, and Zendesk, with access through interfaces such as Claude, ChatGPT, and Cursor. Credal.ai also supports customer-provided Azure OpenAI deployments, self-hosted open-source models, and managed access to models from OpenAI and Anthropic.
Can Credal.ai run on premises?
Credal.ai supports fully on-premises deployment as well as multi-tenant cloud and single-tenant cloud options. Credal.ai states that the appropriate deployment depends on data residency requirements, existing cloud infrastructure, and internal security policies.
How does Credal.ai protect data access?
Credal.ai automatically inherits and enforces existing source permissions at query time. Credal.ai also supports scoped tool access, human approval for sensitive actions, and audit logging, so teams can control which data agents see and which actions agents may perform.
Does Credal.ai have an API?
Credal.ai provides a typed API for connecting governed MCP servers to larger automation chains. Credal.ai also supports embedding agents in custom applications while applying shared identity, permission, and approval rules across supported interfaces.
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