Pega

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Pega is a workflow, case management and decisioning platform that has built its agentic strategy around a deliberately contrarian architectural claim. Pega separates creative AI reasoning at DESIGN time from semantic AI execution at RUN time. Blueprint design agents generate optimised workflows during ideation; at runtime, agents find and follow those approved workflows rather than reasoning freely. Pega argues directly that most agentic solutions deploy AI reasoning at run time and that this introduces unnecessary risk and unpredictability during mission critical work. The pieces fit together in sequence. Pega Blueprint generates workflows and decisioning strategies, usable with a free Pega user ID. Those workflows become Pega Predictable AI Agents through the Pega Agent Experience API. Agentic Process Fabric then acts as the orchestration layer above them, analysing its library of discoverable agents, workflows and data across Pega and non Pega systems and enlisting whichever is best suited to a task. Where no automation exists, it can invoke Blueprint to design a new workflow on the fly under human governance. Users reach these agents through chatbots, email, voice and other channels. Security and deployment are where Pega separates itself from newer entrants. Pega Cloud for Government holds FedRAMP High Authority to Operate, granted in March 2025 after a FedRAMP High In-Process designation, alongside SOC 2 Type 2, ISO 27001, HIPAA and HITECH, PCI DSS, FIPS 140-2 Level 1 cryptographic modules and Department of Defense Impact Level 2. Deployment spans Pega managed cloud, government cloud on AWS GovCloud, client managed cloud using Pega Docker images on any Kubernetes environment, and on premise, with a Cloud Choice Guarantee promising full support and no penalty for migrating between any of them. The honest limits are model transparency and evaluation. No first party model selection or routing surface was retrieved, and while Pega markets predictable outcomes with predictable costs, no agent evaluation harness is documented as a first class capability.