
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.
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.
A structured path from strategy to production
Cresta deployments follow a repeatable approach that helps teams move from planning to production with the right controls in place. Cresta partners with your team at every stage, with the same rigor and safeguards regardless of how hands-on you want to be.
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

A dedicated team, aligned to outcomes
Cresta-managed deployments include a dedicated cross-functional team from day one. They work alongside your stakeholders through every stage, from use case definition to post-launch optimization.

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
FAQ
Who owns what in a customer-managed deployment?
Your team controls configuration, testing, deployment, and iteration within the platform. Cresta provides the tooling, workflows, guardrails, and operational controls needed to run AI agents safely and effectively in production.
How do you manage risk in production?
Before launch, AI agents are thoroughly tested against real customer scenarios. In production, every change goes through a structured release workflow with approvals, versioning, and rollback, and agents are supervised and guided in real-time. Nothing reaches your customers without going through defined controls.
How much effort is required from my internal teams?
The level of effort depends on the operating model. In Cresta-managed deployments, Cresta leads execution end to end with minimal day-to-day involvement from internal teams. In customer-managed deployments, teams work directly in the platform without taking on the burden of building or maintaining AI agent infrastructure.
Can we change operating models over time?
Yes. Many enterprises begin with a Cresta-managed deployment to accelerate time to value, then take on more direct ownership over time as their teams gain confidence and experience.
When does it make sense to buy rather than build AI agents?
Building gives you flexibility, but it also means owning the infrastructure, evaluation systems, and reliability over time. Most enterprises find that the ongoing cost of maintaining that stack outweighs the perceived control. Cresta handles the infrastructure and governance so your team can focus on the use cases that matter to your business.
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.
