Deploy enterprise AI agents with control and clarity
Cresta gives you a structured, repeatable path from strategy to production, with the ownership model, tooling, and controls your enterprise needs to deploy AI agents with confidence.
Choose your operating model
Cresta supports a flexible range of deployment approaches on the same enterprise foundation. The platform, controls, and security don't change. What changes is how Cresta and your team share ownership, and that can evolve as your needs do.
Cresta leads deployment from strategy through optimization, owning delivery, coordination, and outcomes. Your team stays in the loop without carrying the execution. Best for enterprises that want a fast path to production and clear accountability for results.
Cresta builds and launches your first AI agent, then coaches your team to own everything from there. You get the same control as Customer-Managed, without starting from scratch. Best for teams that want to run their own deployment but need a proven first build to launch from.
Your team configures, tests, and deploys AI agents using Cresta’s tooling, workflows, and guidance. You get full control without having to build or maintain the underlying infrastructure. Best for teams that want to own every aspect of their deployment directly.
Meet Conductor:
The agent for AI agent development
Conductor is how Cresta AI agents come to life. Describe what you want in plain language, and it helps your team develop the agent, test it against real scenarios, and refine it as conversations reveal what's working, all in one place, in a fraction of the time. The result is higher-quality agents shipped with fewer people and shorter development cycles, without cutting corners on the rigor enterprise deployments demand. However you choose to work with us, this is the engine behind every deployment.
A structured path from strategy to production
No matter the operating model, Cresta deployments follow a repeatable approach that helps teams move from planning to production with the right controls in place.
Start with a data-backed automation blueprint
Analyze real customer conversations across channels to understand how they unfold from start to resolution
Score automation readiness based on volume, complexity, and resolution rates
Produce a prioritized roadmap aligned to business impact and operational feasibility
Build AI agents as structured, governed systems
Design task-specific subAgents with defined roles, prompts, tools, and objectives to handle complex workflows reliably
Connect securely to backend systems with controlled actions, scoped permissions, and standardized access protocols
Encode guardrails, escalation paths, and compliance boundaries directly in agent behavior
Test the way customers actually use your AI agents
Simulate real customer behavior at scale to surface edge cases early and strengthen reliability
Apply reusable AI-driven evaluators to assess responses against defined quality, policy, and success criteria
Run structured regression tests and enforce release thresholds before shipping updates
Ship changes safely with structured releases
Promote updates through structured release workflows with defined approvals, versioning, and rollback paths
Control how changes reach production, from limited rollout to broader activation
Maintain complete audit history and traceability across prompt changes, tool updates, and agent releases
Optimize performance with outcome-based insights
Prioritize improvements based on measurable business outcomes like resolution, CSAT, sentiment, and conversion
Uncover what’s driving performance changes using AI-powered natural language queries and conversation analysis
Automatically evaluate 100% of interactions against defined standards to maintain quality while iterating and expanding automation
Backed by Cresta expertise
Every deployment is backed by the same Cresta expertise, whether that means a dedicated team from day one or support you call on when you need it. You're never building alone.
Connects business goals to AI Agent execution by partnering with stakeholders to define high-impact use cases, set success metrics, and guide rollout decisions
Owns technical performance in production, tuning models, resolving edge cases, and improving agent reliability over time
Manages governance, milestones, and risk across your business, IT, and operations teams from kickoff through launch
Designs how Cresta AI Agent connects to your enterprise systems, validating integrations, data flows, and architectural decisions end to end
Partners with your team after launch to track outcomes, identify new opportunities, and support long-term value
The deployment experience, from our customers
Chief Executive Officer
Chief Commercial Officer
Vice President of Operations and Shared Services
Senior Director of Resource Management
Chief Executive Officer
Chief Commercial Officer
Vice President of Operations and Shared Services
Senior Director of Resource Management
Frequently asked questions
Who owns what across Cresta's operating models?
How do you manage risk in production?
How much effort is required from my internal teams?
Can we change operating models over time?
When does it make sense to buy rather than build AI agents?
Find the right operating model for your team
Talk to a Cresta expert about your environment, your goals, and which operating model fits where you are today.