Application fit
Place AI where it supports a real workflow.
Related capability
Custom AI Applications
Custom AI-enabled applications built around business workflows and production requirements.
Platform architecture
An application, not a model demo
Custom AI applications combine the user experience with models, context, tools, business rules, data, integrations, and production controls.
User Experienceworkflow / interface
AI Logicgeneration / reasoning
Tools & Integrationsbusiness systems
Data & Retrievalapproved context
Platformdeployment / routing
Controlsevaluation / security
System integration
Connect models to approved data and tools.
Operational control
Measure quality, latency, cost, and failure.
Production control
Design for production from the start
Production quality depends on how the application handles evaluation, permissions, failures, monitoring, cost, and model or workflow changes after launch.
Quality
Evaluation and regression testing.
Cost
Usage and routing visibility.
Security
Access, data, and tool controls.
Operations
Monitoring and lifecycle ownership.
What Gromnii builds
What a custom AI application can include
Build only the AI and engineering components required to create a useful application around the workflow.
01Workflow-centered AI applications
Design the application around a defined business process, user role, and outcome rather than around a model demo.
02Embedded AI features
Add generation, retrieval, prediction, perception, or reasoning inside existing software where it improves the user’s task.
03Enterprise data and retrieval
Connect approved data, knowledge, context, and permissions so model output reflects the information the application is allowed to use.
04Tools and system integration
Give the application controlled access to APIs, workflows, CRMs, ERPs, databases, or internal services when the task requires action.
05Evaluation and reliability
Define quality tests, failure handling, monitoring, and regression checks before the application becomes operationally important.
06Security and lifecycle operations
Design identity, access, logging, cost visibility, updates, and ongoing support into the production environment.
Discuss the requirement.
This page remains available for requirements that combine several AI techniques and do not fit a single named capability.