API & application integration
Embed AI functions into CRM, ERP, portals, mobile apps, web products, and internal systems.
Connect models, agents, copilots, and machine learning services to enterprise applications, data platforms, APIs, identity, workflow engines, and customer channels without creating a disconnected AI layer.
Etelligens maps the systems, data, roles, permissions, events, actions, and operational constraints around the target workflow.
We build integration layers that can manage model providers, data access, orchestration, business rules, retries, observability, security, and version changes while keeping core applications maintainable.
The result is an AI capability that behaves like part of the enterprise architecture—with clear ownership, interfaces, monitoring, and failure handling.
Integration can be delivered as an API layer, event-driven workflow, embedded product feature, platform service, or modernization program.
Embed AI functions into CRM, ERP, portals, mobile apps, web products, and internal systems.
Connect warehouses, lakes, operational stores, vector databases, search, and streaming sources.
Apply authentication, authorization, tenant boundaries, role-aware context, and data access policies.
Abstract providers, manage keys and policies, route tasks, and support model changes without rewriting applications.
Combine AI outputs with business rules, queues, approvals, notifications, and deterministic services.
Monitor performance, errors, model calls, cost, data flows, retries, fallbacks, and service-level behavior.
Integration creates value by moving AI from an isolated interface into the point where decisions and actions already happen.
Surface recommendations, summaries, next-best actions, and knowledge inside agent workflows.
Automate classification, exception handling, planning inputs, and operational decision support.
Embed search, recommendations, assistants, content intelligence, and predictive features into customer experiences.
Connect predictive and generative capabilities to governed data products, dashboards, and decision workflows.
Our multidisciplinary team connects product strategy, data, AI engineering, application integration, security, quality engineering, and change management.
Document systems, data contracts, users, workflows, security boundaries, and non-functional requirements.
Select interfaces, orchestration, model abstraction, identity, data access, observability, and fallback patterns.
Implement services, adapters, workflows, tests, monitoring, and environment-specific configuration.
Track reliability, model behavior, dependencies, cost, and usage while supporting controlled evolution.