Building your first agent is straight forward. Governing your hundredth is not.
The first AI agent proves the concept. The tenth introduces coordination problems. The hundredth becomes an enterprise governance challenge. CAMS AgentOps is the platform that makes scaling AI agents from one to one hundred as controlled and auditable as your very first production deployment.
The challenges that appear as you scale.
Deploying one agent is a technical exercise. Scaling agents across an enterprise is an organizational, governance, and infrastructure challenge. Most platforms address the first problem competently. Very few address what happens when you try to go from ten agents to a hundred agents.
Team A builds their own evaluation framework. Team B creates their own monitoring setup. No shared standards. No unified governance model.
Without a standardized evaluation process, there is no consistent bar for what constitutes a production-ready agent.
As the number of agents grows, so does the invisibility of what they are doing collectively. Leaders do not have centralized oversight.
A procurement agent and a vendor risk agent should exchange information. But they don't because they were built with different data models.
When every agent defaults to the most capable model, and no per-agent cost telemetry exists, the compounding cost of LLM inference is invisible.
When your auditor, regulator, or board asks which AI systems are operating and how they are governed, the answer is not readily available.
One complete agent lifecycle platform.
Each AgentOps component handles one stage of the agent lifecycle. Deploy them progressively as your programme matures, or as a complete integrated system from the start. Either way, your agents are built, tested, registered, deployed, and monitored through shared infrastructure.
Visual flow builder for teams that think in processes. Pre-built templates for common enterprise patterns. Drag-and-drop tool binding to any data source, model, or API.
Explore Agent Studio →Automated test suite generation, adversarial prompt testing, hallucination rate measurement, bias detection, and regression testing for updates. Every agent receives a production readiness assessment.
Explore AgentEval →Central catalog for every deployed agent. Metadata management, role-based access control, and automated guardrail checks covering PII handling, data residency, and model licensing. Complete audit trail of every state change.
Explore Agent Registry →Internal marketplace where registered agents are published and made discoverable. API endpoint generation, versioning, usage analytics per agent, and internal versus external visibility controls.
Explore Agent Marketplace →DAG-based workflow composition, parallel and sequential agent execution, cross-agent context passing, retry and fallback logic, human-in-the-loop escalation triggers, and event-driven activation.
Explore OrchestratAI →Real-time dashboards configurable by business persona. Natural language querying of agent performance. Threshold-based alerting when performance drops or bias drifts.
Explore AI Agent Control Tower →One platform. The right interface for each person using it.
AgentOps is role-aware by design. A business leader uses AI Agent Control Tower's plain-language dashboards. An AI engineer uses Agent Studio's SDK. A compliance officer runs AgentEval governance reports. Same platform, different entry points.
StrategyCompass for use case prioritization. AI Agent Control Tower for agent performance oversight. Agent Registry for governance policy enforcement.
Agent Studio for building and versioning agents. AgentEval for automated testing before production. OrchestratAI for wiring agents into multi-step business workflows without boilerplate infrastructure.
AgentEval bias and safety reports. Agent Registry guardrail enforcement. AI Agent Control Tower audit trail and instant kill switch. Full traceability from the data input through to every agent action.
Agent Marketplace for publishing agent capabilities. Usage analytics, API versioning, and access control management. Insight into which agents are being consumed and by whom.
compared to building independently.
Questions that AI engineering leaders ask us
If your question is not here, our platform engineering team will answer it directly.
Talk to a platform engineer →Agent sprawl occurs when AI agents are deployed across business units without central coordination, each with its own tooling, governance approach, and data handling. The result is an AI estate that no one can see completely, where compliance is inconsistent, and regulatory accountability is undefined. CAMS prevents agent sprawl through the Agent Registry, which maintains a governed record of every agent in your estate, and AI Agent Control Tower, which gives leadership real-time visibility and intervention capability across all of them.
AgentEval is the mandatory governance gate that every CAMS agent must pass before reaching production. It runs an automated test suite covering bias detection, adversarial prompt testing, hallucination rate measurement, and latency profiling. The output is a production readiness certification with a documented pass record. No agent moves from Agent Studio to the Agent Registry without clearing AgentEval, which means every agent that ships has cleared the same documented bar.
CAMS AgentOS provides the technical infrastructure that the EU AI Act requires. The Agent Registry maintains the documentation record every deployed agent needs under the Act's transparency obligations. AgentEval produces conformity assessment evidence for high-risk systems. AI Agent Control Tower provides the human oversight and intervention capability that the Act mandates. For enterprises with phased compliance deadlines through 2026 and 2027, the governance architecture is built in from day one.
You can do both. CAMS is available as a development platform for your engineering team to build proprietary AI products, and Covasant's own products, konaAI, TPRM, ARIIA, CyberProTX, are also available for deployment. Your team uses Agent Studio for building, using the same infrastructure and governance pipeline that powers every Covasant product. You can run both simultaneously; deploy existing products for immediate value while building proprietary agents on the same platform in parallel.
AI Agent Control Tower provides real-time dashboards by role and persona, natural language querying of agent performance across the estate, threshold-based alerts, and an instant kill switch at agent, workflow, or estate level. Every action taken by any agent is logged with timestamps and decision rationale, creating an audit trail that is assembled automatically rather than reconstructed after the fact. For CTOs and CISOs accountable for AI in production, the AI Agent Control Tower is the governance interface that makes that accountability manageable.
Watch an agent go from use case to production in one demo.
We will walk your AI and engineering leadership through a live AgentOps session. From use case mapping in StrategyCompass to an agent running in production under the oversight of AI Agent Control Tower.