API & application integration
Embed AI functions into CRM, ERP, portals, mobile apps, web products, and internal systems.
etelligensAi · Enterprise integration
Integrate AI into the systems, workflows, and experiences your business already depends on.
AI integration connects model capabilities with enterprise applications, approved data sources, and business processes.
Business-value firstSecurity & governance by designProduction engineeringMeasured adoption
Why it matters
AI adoption accelerates when intelligence is embedded into existing work instead of forcing users into separate tools.
Validate authentication, schema contracts, timeouts, retries, and data-handling boundaries for each connected system.
An integration is incomplete until failures have a defined operational path.
Capabilities
What Etelligens delivers.
Integration can be delivered as an API layer, event-driven workflow, embedded product feature, platform service, or modernization program.
Data platform connectivity
Connect warehouses, lakes, operational stores, vector databases, search, and streaming sources.
Identity & permissions
Apply authentication, authorization, tenant boundaries, role-aware context, and data access policies.
Model gateway & routing
Abstract providers, manage keys and policies, route tasks, and support model changes without rewriting applications.
Workflow orchestration
Combine AI outputs with business rules, queues, approvals, notifications, and deterministic services.
Observability & resilience
Monitor performance, errors, model calls, cost, data flows, retries, fallbacks, and service-level behavior.
Enterprise use cases
Where this capability creates value.
Integration creates value by moving AI from an isolated interface into the point where decisions and actions already happen.
CRM & service platforms
Surface recommendations, summaries, next-best actions, and knowledge inside agent workflows.
ERP & operations
Automate classification, exception handling, planning inputs, and operational decision support.
Digital products
Embed search, recommendations, assistants, content intelligence, and predictive features into customer experiences.
Data & analytics
Connect predictive and generative capabilities to governed data products, dashboards, and decision workflows.
Delivery model
From opportunity to reliable production.
Our multidisciplinary team connects product strategy, data, AI engineering, application integration, security, quality engineering, and change management.
Map
Document systems, data contracts, users, workflows, security boundaries, and non-functional requirements.
Architect
Select interfaces, orchestration, model abstraction, identity, data access, observability, and fallback patterns.
Build
Implement services, adapters, workflows, tests, monitoring, and environment-specific configuration.
Operate
Track reliability, model behavior, dependencies, cost, and usage while supporting controlled evolution.
What clients say about us
Trusted for responsiveness, delivery quality, and ownership.
Feedback from clients who have worked with Etelligens across application development, web platforms, branding, and complex software delivery.
01
Praised the team’s responsiveness, willingness to go beyond the agreed scope, and the quality of the completed application.
Joshua HarrisEtelligens client
02
Highlighted the quality of the website, strong troubleshooting, fast understanding of requirements, and a positive overall delivery experience.
Dean EdelsonEtelligens client
03
Commended the booking-application team for identifying overlooked issues, exceeding expectations, and delivering a polished finished product.
Dr. Matthew MaggioEtelligens client
04
Said the team captured the brand’s identity effectively, communicated promptly across Western time zones, and earned continued work on product and service branding.
Joel LogicEtelligens client
05
Described the team as highly capable and accessible, crediting them with rescuing a difficult software project and consistently going the extra mile to deliver on time.
SargeEtelligens client
06
Highlighted faster-than-expected delivery, close adherence to requirements, and strong communication throughout the web-development project.
Christopher SandsEtelligens client
1 / 2
Connect AI to the systems and workflows where it can create measurable value.
Talk to our AI team ↗Frequently asked questions
AI Integration Services: questions before you start
Practical answers on scope, delivery choices, and acceptance.
AI integration connects model capabilities with enterprise applications, approved data sources, and business processes. The agreed scope can include AI delivery scope, data readiness, evaluation, and rollout controls.
Validate authentication, schema contracts, timeouts, retries, and data-handling boundaries for each connected system. Bring the current workflow, important constraints, and the decision or user outcome you need to improve.
An integration is incomplete until failures have a defined operational path. Ask the delivery team to explain the alternatives, exclusions, and evidence that would change its recommendation.
Scope, integration dependencies, data readiness, access approvals, and acceptance requirements determine the estimate. For this work, plan explicitly for AI delivery scope, data readiness, evaluation, and rollout controls. Request milestones and assumptions rather than an unsupported fixed-price promise.
Agree acceptance evidence before implementation. Validate authentication, schema contracts, timeouts, retries, and data-handling boundaries for each connected system. Record known limitations, unresolved risks, ownership after handoff, and the next review point.
Delivery evidence
Connect the scope to real work.
An integration is incomplete until failures have a defined operational path. Related capabilities include Security Testing Services.