Deploying enterprise AI teammates through MCP with Clarifeye
B2B
Agent builder
Regulatory & manufacturing
Clarifeye builds enterprise AI teammates for high-stakes workflows where accuracy and explainability matter. Rather than UI or orchestration, it delivers a knowledge layer that captures and evolves organizational judgment. Using MCP with Alpic’s deployment infrastructure, Clarifeye deploys secure, auditable AI directly into customers’ existing tools, without rebuilding frontends, so teams get expert-level AI where they already work.
What Clarifeye’s AI teammates do:
Clarifeye’s AI teammates support complex, multi-step decision processes across domains such as regulatory, safety, quality, operations, etc.
These use cases typically require:
Applying company-specific rules and judgment
Maintaining clear decision traceability
Adapting continuously as policies, context, and edge cases evolve
The result is AI that behaves consistently across the organization, not just answers questions.
Each deployment adapts to the customer’s internal processes, data sources, and decision logic.
This is why Clarifeye emphasizes explainability, auditability, and governance, not as features, but as prerequisites for AI teammates operating in real, high- stakes environments.
The challenge
Clarifeye’s AI teammates capture how organizations reason, decide, and apply expertise — but bringing that intelligence to enterprise users at scale posed a distribution challenge. Most customers already work within existing AI environments such as copilots, internal assistants, or collaboration tools like Microsoft 365, Claude, or ChatGPT. Rebuilding bespoke frontends for each environment is costly and slows adoption.
Clarifeye’s experiments with “Clarifeye inside” on Claude demonstrated potential but also revealed user experience constraints: repetitive tool confirmation prompts and limited multi-step workflow execution. A robust distribution layer was needed, and exposing their services directly via MCP was the most viable long-term solution.
Why MCP
MCP has become the shared protocol layer across major AI ecosystems. As enterprises converge on AI copilots, the competitive advantage lies not in building new frontends, but in delivering robust, explainable backends that can plug into those ecosystems. For Clarifeye, using MCP ensures their teammates can integrate seamlessly into environments where customers already work, without sacrificing compliance visibility or audit control.
The role of Alpic
Alpic provides the infrastructure layer for MCP, enabling any MCP server or agent backend to be deployed, scaled, and monitored in production.
For Clarifeye, Alpic offers:
MCP-native hosting to deliver their AI teammates directly into customers’ preferred frontends.
Secure, isolated environments that meet the requirements of regulated and high-stakes operations.
Reusable infrastructure to standardize distribution and avoid maintaining one-off integrations.
By eliminating the complexity of deploying a custom MCP server for each of Clarifeye's clients, Alpic allows Clarifeye to stay focused on what truly differentiates them — building precise, explainable AI teammates that capture and evolve organizational knowledge.
For us, it’s natural to work with Alpic. They already have the infrastructure, the expertise, and the reliability we need. That let us concentrate fully on what defines Clarifeye capturing, explaining, and evolving organizational judgment.