Impetus outlines its Context Engineering Delivery Lifecycle for AI agents

Impetus Technologies has outlined the Impetus Context Engineering Delivery Lifecycle, or CEDL, as its method for supplying enterprise-specific context to AI agents. In an August 15 interview with SiliconANGLE, Deepak Khosla, the company’s chief growth officer and head of AI, said the approach is intended to connect agentic systems with an organization’s data, business knowledge and operating rules. No funding, valuation or financial figures were disclosed.

Impetus frames the problem as a “context gap” between general-purpose model knowledge and the proprietary data, workflows, regulatory constraints and domain expertise held by an enterprise. That is the company’s diagnosis and positioning, rather than an independently tested finding.

What is Impetus’s Context Engineering Delivery Lifecycle?

Khosla described CEDL as a recurring process: create the context agents need, engineer that context into the system, observe what is and is not working, then use those signals to improve subsequent agent behavior. The supplied material does not provide a technical specification, architecture validation or benchmarks for the methodology.

Operationally, Impetus says the framework combines several familiar enterprise AI workstreams: modernizing legacy data systems, defining semantic meaning, constructing knowledge graphs and ontology layers, managing memory, orchestrating agents, and applying testing and governance. Khosla said both short- and long-term memory require attention because incorrect information retained by a system may affect later actions.

The company groups its diagnosis into four gaps:

• Data: legacy information that Impetus says is siloed, inconsistently governed or difficult for AI systems to access.
• Semantic: missing definitions and relationships that explain what enterprise data means in a business setting.
• Execution: context drift during handoffs, limited observability and governance weaknesses, according to Impetus.
• Trust: the need for controls, auditability and enterprise-specific guardrails, in the company’s view.

How do Leap AI and Context Fabric fit together?

Impetus positions Leap AI as a broader family of software-led services spanning modernization, semantic context, agent solutions and observability. SiliconANGLE reported in May that Impetus had launched the Leap AI family, also in a sponsored interview segment. The August discussion of CEDL described a methodology, not a separate product launch.

Within that product framing, Impetus describes Context Fabric as its context-engineering platform. The company says it can extract meaning from enterprise data, build knowledge graphs and semantic layers, and deliver structured context to AI agents and large language models at inference time. It also lists retrieval, memory configuration and isolation controls among the platform’s capabilities.

Those claims remain vendor assertions. SiliconANGLE identified both interviews as sponsored by Impetus, while saying sponsors did not have editorial control. The supplied material contains no pricing, general-availability, customer-deployment or independently verified performance details. It also offers no independent reliability data, defined deployment scope, verified customer outcomes, or benchmarks against alternative approaches.

This story draws on original reporting from SiliconANGLE.