Build the knowledge, applications, and controls behind
an Agentic Enterprise.
We structure business rules and data, assess platform options and operating requirements, then engineer the agents, applications, and system integrations needed to put them into use.
Four services connect business knowledge to deployed agents and applications
Knowledge engineering structures the business rules and evidence. Platform assessment defines the architecture. Application development puts the knowledge and data to work. AgentOps governs operations after deployment.
Enterprise Knowledge Engineering
Structure policies, documents, data definitions, and expert judgment into verifiable knowledge assets with traceable sources, approval, and change control.
View the service →AI Platform Assessment & Architecture
Assess the use case, knowledge and data readiness, security, existing systems, and operating responsibilities before defining the target architecture.
View the service →Agentic Analytics & Applications
Build agents and applications that detect change, investigate causes, assess impacts, and present evidence and alternatives for review.
View the service →AgentOps & Managed Operations
Manage evaluation, permissions, execution history, quality, cost, incidents, and change after deployment.
View the service →Make business rules and expert judgment usable by agents and reviewable by people
We map business concepts and relationships, then structure Business Rules, exceptions, sources, and judgment criteria in an Ontology and Knowledge Graph. Validation, approval, and change control are built into the model.
LLMs can support this work, but the business purpose and Knowledge Model are defined first. The design is not tied to a particular graph product.
Discuss Knowledge Engineering →Choose the platform based on the use case and operating requirements
We examine the priority use case, knowledge and data readiness, security requirements, existing systems, and operating responsibilities. We then compare Snowflake, Cloud AI, and on-premises platforms and define the platform approach, target architecture, and implementation roadmap.
Discuss Platform Assessment →Build agents that prepare analysis, evidence, and alternatives for action
Agents use business knowledge and data to detect change, investigate causes, and assess the impact. Forecasting, simulation, and optimization models can be combined with agents and business applications so users can review evidence and alternatives and carry the result into the next step in the workflow.
Discuss an Agentic Application →Operate agents with defined evaluation, permissions, and change control
Before deployment, we define evaluation and approval criteria. During operation, we manage permissions, execution history, quality, performance, cost, incidents, and changes to agents, knowledge, and business rules. Depending on the client’s operating model, the scope may include an AgentOps foundation or Managed Operations.
Discuss AgentOps →Business context determines the agent’s role
Our experience spans enterprise transformation, ERP, BI and data warehousing, data governance, management control, and systems implementation. That context helps us identify the user questions, evidence, approval points, and exception handling that the solution must reflect.
Knowledge confirmed during delivery is managed as Project Knowledge. Only validated material is incorporated into the Knowledge Graph and standards. This helps distinguish the agent’s work from tasks that require human review and decision authority.
Snowflake services for the data foundation behind analytics and AI
We also provide Snowflake services for data foundations, SAP migration, data engineering and integration, and ongoing cost and platform operations.
AI-Ready Data Foundation
Establish data quality rules, standards, lineage, security, and access controls in Snowflake.
Discuss the scope →SAP to Snowflake Migration
Assess SAP ECC, S/4HANA, and BW data, then migrate and validate it in Snowflake.
Discuss the scope →Data Engineering & Integration
Connect ERP, MES, SCM, CRM, and external sources through data pipelines built for ongoing use.
Discuss the scope →FinOps & Managed Services
Manage Snowflake costs, performance, security, data pipelines, and changes over time.
Discuss the scope →Start with the workflow, knowledge, and data you have today
Tell us which workflow or decision you are examining, how the relevant rules are documented, which data and systems are involved, and who reviews the result. We will help identify whether the first need is knowledge engineering, platform assessment, an application build, or AgentOps.
Discuss an Agentic Enterprise Initiative →