User Interfaces: Conversational, Generated, Personalized, Micro UIs
Machine Interfaces: Headless Machine Interfaces (e.g., HTTPS, A2A, MCP)
Unified Session Management, Omnichannel Connectivity, Shared Event Manager, Voice Gateway
Independent Short-Term and Long-Term Memory, Decoupled from Models and Shared Across Applications
Spaces, Flow Steps,
and Agents
AI Applications:
Agents and Workflows
(Probabilistic and Deterministic)
AI Models:
Lookup and Canonical
Knowledge Management
Local Knowledge and Tools
(e.g., Lookup Vector DB)
Knowledge Integration
External Knowledge and Tools
Intelligent Digital Workers and Agents
Human–AI Collaboration
Self-Composing, On-Demand, Auto-Scaling, End-to-End Hosting and Infrastructure
Provides real-time visibility into AI agent behavior, system performance, and execution flows, enabling rapid troubleshooting and continuous optimization.
Maintains and synchronizes shared sessions across AI agents, workflows, systems, and channels to ensure consistent, context-aware experiences.
Orchestrates real-time events and triggers across AI agents, workflows, and integrations, enabling coordinated, responsive system behavior.
Delivers operational and business insights into AI agent usage, outcomes, performance, and efficiency to inform optimization and decision-making.
Defines and enforces policies for AI agent behavior, model usage, data access, and human oversight across the platform.
Implements enterprise-grade protections across data, AI models, and infrastructure, including encryption, isolation, and continuous monitoring.
Manages role-based and policy-driven permissions for users, AI agents, and systems, ensuring least-privilege access and regulatory compliance.
A visual, low-code/no-code environment that enables both developers and users to design, deploy, and iterate agentic workflows without heavy engineering effort.
A reusable catalog of proven AI agent templates, workflows, and enterprise integrations that accelerates time to value and reduces implementation risk.
Built-in versioning allows teams to track changes, compare iterations, and safely roll back to previous versions, supporting controlled experimentation and rapid recovery.
Provides real-time and historical insights into AI agent performance, user interactions, outcomes, and operational metrics to drive continuous optimization.
Tools for designing, testing, and managing prompts and retrieval-augmented generation pipelines, enabling grounded, context-aware responses using enterprise data.
Comprehensive logging and audit trails capture AI agent decisions, actions, and data access, supporting compliance, traceability, and operational governance.
Built-in testing frameworks enable simulation, scenario testing, and validation of AI agent behavior before and after deployment, reducing risk in production environments.
User Interfaces are human-centric interaction layers that enable people to engage with AI agents naturally and contextually, adapting in real time to user intent, role, and workflow state.
Natural language interfaces across voice, chat, and messaging that allow users to interact with AI agents conversationally, with continuous context and real-time responsiveness.
Dynamically created UIs that are assembled at runtime to accomplish the user’s goals based on their preferred channel, desired outcomes, and real-time conversational context.
Interfaces that adapt in real time to each user’s role, preferences, history, and permissions, delivering relevant information and actions without unnecessary friction.
Task-specific UI components (forms, cards, confirmations, prompts) embedded seamlessly within conversations or workflows to capture input and drive decisions efficiently.
Machine Interfaces enable secure, non-visual, programmatic communication between AI agents, models, and enterprise systems, supporting real-time coordination, orchestration, and context exchange across distributed environments.
Communication Fabric is the platform layer that unifies every customer and employee interaction channel into a single, continuous experience.
Maintains a single, continuous session across AI agents, channels, and systems, preserving context, state, and identity throughout the entire interaction lifecycle.
Enables seamless communication across voice, chat, SMS, web, mobile, and enterprise systems, allowing users and AI agents to move between channels without losing context.
Coordinates real-time events, signals, and state changes across AI agents, workflows, and integrations, ensuring consistent behavior and synchronized decision-making.
Provides enterprise-grade voice connectivity with support for real-time streaming, barge-in, transcription, and handoffs between AI agents and humans.
Contextual Memory System is the platform layer that captures, preserves, and shares contextual knowledge across interactions, enabling AI agents to reason in the moment while retaining long-term user, task, and system memory.
Maintains both transient, in-session memory and persistent, cross-interaction memory to support real-time reasoning while retaining long-term knowledge and user context.
Memory is model-agnostic and centrally managed, allowing multiple AI models and applications to access and reuse shared context without duplication or lock-in.
AI agents and orchestrated workflows combine probabilistic reasoning with deterministic logic to handle both open-ended interactions and rule-based execution, enabling reliable automation alongside adaptive decision-making.
In addition, by layering large language models (probabilistic) over hard-coded business rules and workflows (deterministic), the platform delivers high-accuracy responses that remain flexible enough to handle open-ended inquiries while strictly adhering to enterprise compliance and policy.
OneReach.ai Cognitive Orchestration Engine is the platform layer that dynamically selects, invokes, and coordinates the most appropriate AI models and cognitive services at runtime, enabling AI agents to adapt in real time across tasks, contexts, and vendors without lock-in.
Enterprise-managed models deployed within controlled environments to meet strict requirements for data privacy, security, latency, and regulatory compliance.
Cloud-based models accessed via secure APIs, enabling rapid access to state-of-the-art capabilities while maintaining governance, observability, and flexible model selection.
Secure access to enterprise-owned knowledge sources and tools, including structured data, documents, and vector databases, to ground AI agents in trusted, up-to-date information.
Governed connections to external data sources, APIs, and services that extend AI agent capabilities while enforcing access controls, validation, and usage policies.
Intelligent Digital Workers are AI agents that collaborate with one another across any channel or language to seamlessly execute tasks and create cohesive user experiences.
OneReach.ai Human-in-the-Loop is the platform layer where AI agents and people collaborate within the same workflows, enabling humans to guide decisions, resolve edge cases, train agents from live conversations, and ensure accuracy, trust, and compliance.
Organizations can run GSX in unique, isolated instances within specific geographic regions or directly within their own AWS virtual private clouds.
Automatically assembles the required infrastructure components, such as compute, storage, networking, AI models, and services, based on workload and configuration needs.
Environments can be provisioned, modified, or decommissioned as needed, enabling rapid experimentation and deployment without manual infrastructure management.
Dynamically scales resources up or down in real time to match demand, ensuring consistent performance while optimizing cost.
Provides fully managed hosting across the entire stack, from infrastructure and runtime services to AI models and integrations, eliminating operational complexity for enterprise teams.
Private, isolated deployment environments running on customer-selected cloud platforms, data centers, and dedicated hardware, where the use of AI tokens or cloud compute is fully owned and controlled by the customer, ensuring predictable costs alongside performance, security, and regulatory compliance.