For Systems Engineers
Eliminate Developer Toil and Unleash Productivity.
Enabling enterprise-grade contextual automation in a distributed system is wicked hard – EnterpriseWeb just makes it look easy.
The Semantic AI Harness is a no-code platform for systems engineers, solution architects and ontologists. It shifts routine and tedious technical tasks from those specialists to the runtime, which takes responsibility for implementing all related engineering concerns.
The power of EnterpriseWeb stems from the fact that it’s no-code design environment supports the declarative modeling of executable behavior (e.g., functions, algorithms, workflows), as machine-readable typed objects in the same graph and runtime, under common governance, alongside domain concepts in the ontology and entities in the knowledge graph. In this way EnterpriseWeb bridges Knowledge Engineering and Systems Engineering and enables real-time, Enterprise-grade contextual automation. EnterpriseWeb’s was intentionally designed from the ground up for metaprogramming, autonomic policy-controlled closed-loops and autonomous systems. The company has been awarded 23 US patents, additional patents pending.
Safe transaction primitives.
EnterpriseWeb leverages Metaprogramming and advanced Functional Programming for generating high-level implementations of critical, distributed systems functions (e.g., loops, promises, transitions, sagas, immutability, idempotency), making them safe transaction primitives with managed side-effects; eliminating the most challenging aspects of platform engineering.
EnterpriseWeb’s platform abstraction (i.e., metamodel, type system and libraries) handles system-wide governance (i.e., cross-cutting concerns). It wraps all typed, immutable objects with security/identity, change and lifecycle management, and all event-driven, asynchronous transactions with security/access control (role and attribute-based), reliable messaging, transaction guarantees, state management and logs and distributed traces linked to records.
EnterpriseWeb arms developers with powerful abstractions (i.e., primitives, building blocks and services) that enable the declarative design, deployment and management of complex, event-driven distributed processes. They allow developers to focus on composition, flows and policies while the runtime handles implementation details, including continuous assurance and optimization.
Context-as-a-Service, not manual engineering.
The Semantic AI Harness also provides abstractions that ease and speed the design, use and maintenance of ontologies, topologies and knowledge graphs. Instead of manual context engineering, it enables Context-as-a-Service. EnterpriseWeb replaces tedious development of primitive and expensive loops over a language model with knowledge-driven platform services that use recursion to reduce complex arrays (i.e., highly dimensional, conditional, and sparse graph) to a list. This allows EnterpriseWeb to efficiently hydrate global context for stateless, ephemeral functions.
Neuro-Symbolic AI, in practice.
In addition, EnterpriseWeb uses high-level abstraction to hide the complexity of Generative and Agentic AI. The Semantic AI Harness, leverages the combined capabilities of its Knowledge Plane and Control Plane, to dynamically orchestrate language models and coordinate agents. It is a novel and advanced form of Neuro-Symbolic AI in which Symbolic AI acts as a control language, providing coherence, consistency, coordination and control over a complex distributed system (i.e., system of systems), which includes connected language models as inference service endpoints and agents as system clients. Language models and agents are simply other types of objects that are declaratively composable, along with people, information, capabilities and policies, for enterprise-grade, contextual business operations.
Every interaction is a Complex Event.
The Semantic AI Harness provides a system-wide listener. Requests, events and prompts are handled by the Context Engine, which acts as an intent-based behavioral interface. Every interaction triggers the Context Engine, which uses in-band metadata to bootstrap the traversal of the Knowledge Plane to wrangle related objects, including entities, tasks, tools and policies to advance the processing. The runtime resolves all references to typed objects, translates policies, and executes embedded queries, functions and service calls as declaratively specified to late-bind a contextual response. In effect, every interaction is a Complex Event, and EnterpriseWeb performs Hybrid Transaction and Analytics Processing (HTAP) to deterministically interpret intent, evaluate condition, translate policies and optimize actions. Unlike language models and manually engineered loops, EnterpriseWeb’s methods are highly reflective and deeply recursive. They enable hyper-efficient reasoning across a complex domain.