Intellectyx Logo
Build AI around your enterprise

Enterprise AI Development Services for Production-Ready AI

Move from a validated AI opportunity to a secure, integrated, production-ready solution. Our enterprise AI development services help organizations design, build, evaluate, integrate, and deploy AI applications around their workflows, data, systems, and business requirements.

From Agentic AI and Generative AI to enterprise knowledge systems and custom AI applications, IX AI combines AI engineering with enterprise integration to move solutions beyond prototypes and into real business use.

Discuss Your AI Development ProjectExplore AI Development
AI development services

Trusted by Our Clients

DQLabs logo
Arria logo
Helix AI logo
Church Community Builder logo
HunterLab logo
People Element logo
Complykey logo
Babies Count logo
DQLabs logo
Arria logo
Helix AI logo
Church Community Builder logo
HunterLab logo
People Element logo
Complykey logo
Babies Count logo
Who this is for

When enterprise AI development can help

You have an AI use case ready to build

The opportunity has been defined, and your team needs the architecture, engineering, integration, and evaluation required to turn it into a working solution.

Your AI pilot needs to reach production

A prototype has demonstrated potential, but security, permissions, integrations, evaluation, governance, or scalability still need to be addressed.

You want AI agents to perform business workflows

Your use case requires AI to reason across steps, use tools, work with enterprise systems, and involve people at defined decision points.

You need AI built around proprietary processes

Standard products do not fully match your workflows, data, industry requirements, or existing applications.

What we do

Enterprise AI Development Services

Our services can be used individually or combined when an enterprise AI solution requires multiple capabilities.

01

Agentic AI Development Services

Build AI agents that can reason, use tools, coordinate tasks, interact with enterprise systems, and complete multi-step workflows within defined business and governance boundaries.

We design agentic applications around the actions the agent needs to perform, the information it can access, the systems it can use, and the points where human approval should remain in place.

You receive
  • An agent architecture aligned with the target workflow
  • Agent roles, tools, permissions, and decision boundaries
  • Enterprise system and API integrations
  • Human approval and escalation checkpoints
  • Evaluation and regression criteria for agent behavior
  • A production-ready agent workflow with operational documentation
02

Generative AI Development Services

Develop AI applications that can understand, extract, summarize, draft, generate, and work with unstructured enterprise content.

We build Generative AI solutions for knowledge-intensive and document-heavy workflows using the models and application architecture best suited to the business requirement.

You receive
  • A Generative AI application aligned with the business workflow
  • Model and architecture recommendations
  • Prompting and structured output workflows
  • Document or multimodal processing capabilities
  • Guardrails and response controls
  • Evaluation criteria for quality and reliability
03

Enterprise Knowledge AI

Connect employees, customers, applications, and AI agents with trusted enterprise knowledge.

We build enterprise knowledge systems using approaches such as RAG, Agentic RAG, Graph RAG, knowledge graphs, and enterprise search while accounting for permissions, source quality, citations, and information freshness.

You receive
  • An enterprise knowledge architecture
  • A retrieval strategy designed for the use case
  • Permission-aware access to approved information
  • Document ingestion and indexing workflows
  • Grounding and source citation capabilities
  • Retrieval evaluation and quality controls
04

Custom AI Development Services

Build AI solutions around proprietary workflows, applications, data, and business requirements that are not effectively addressed by off-the-shelf products.

Our custom AI development services can support predictive applications, workflow automation, embedded AI, decision-support systems, and AI capabilities integrated into existing enterprise products.

You receive
  • A custom AI architecture aligned with your requirements
  • AI and machine learning components built for the use case
  • Integration with enterprise applications and data
  • User-facing or embedded AI functionality
  • Testing, evaluation, and deployment support
  • Documentation and operational handover
Experience and delivery

AI engineering grounded in enterprise delivery experience

Our AI development work combines AI engineering with experience across enterprise applications, data platforms, integrations, cloud environments, and business systems.

That helps us address the production requirements that sit around the model, including identity, permissions, integrations, evaluation, traceability, security, cost control, and operational readiness.

16+
Years in operation
500+
Global clients
600+
Projects delivered
150+
AI Solutions Delivered
Engagement formats

Choose a development model that fits your AI initiative

AI PoC / MVP

Test the most important technical or business assumption against relevant data before committing to a larger implementation.

Typical duration
4 to 8 weeks
Best for
New AI concepts or higher-uncertainty use cases
Output
Working prototype and feasibility findings
Most comprehensive

Custom AI Solution Development

Design, build, integrate, evaluate, and deploy a complete AI application within your enterprise environment.

Typical duration
8 to 16 weeks
Best for
Defined AI use cases ready for implementation
Output
Production-ready AI solution

AI Innovation POD

A multidisciplinary AI team working continuously across your prioritized AI development backlog.

Typical duration
Monthly
Best for
Organizations with an ongoing AI roadmap
Output
Continuous AI engineering and delivery

Stalled Build Recovery

Assess an AI implementation that is struggling to reach production and determine what needs to change.

Typical duration
2 to 4 weeks
Best for
Existing AI builds with architecture, integration, evaluation, or governance issues
Output
Findings and remediation plan
Deliverables

Practical outputs built for implementation

An enterprise AI development engagement should leave your team with a working solution and the assets required to deploy, evaluate, operate, and improve it.

Production AI solution

A working agent, Generative AI application, enterprise knowledge system, or custom AI application designed around the selected workflow.

Enterprise integrations

Connections to the systems, APIs, applications, knowledge repositories, and data required by the solution.

AI architecture

Documented technical direction covering models, orchestration, data, integrations, security, deployment, and operational dependencies.

Evaluation framework

Test cases, golden datasets, quality criteria, trajectory tests, and regression checks appropriate to the use case.

Security and permission model

Defined access controls, tool permissions, data boundaries, and human approval points.

Deployment and handover

Deployment support, documentation, runbooks, evaluation assets, and operational guidance.

Our process

A structured path from AI use case to production

  1. 01

    Discover

    Confirm the workflow and success criteria

    Review the business process, users, systems, data, constraints, and baseline measures that will define the solution.

  2. 02

    Design

    Define the AI architecture and boundaries

    Plan the model approach, agent responsibilities, integrations, permissions, human checkpoints, and evaluation criteria.

  3. 03

    Build

    Engineer the AI solution

    Develop the application around your workflows, terminology, business rules, data, exception handling, and user requirements.

  4. 04

    Integrate

    Connect AI to enterprise systems

    Integrate the solution with applications, APIs, systems of record, knowledge repositories, and data platforms under the required security model.

  5. 05

    Evaluate

    Test performance against defined requirements

    Evaluate the solution using representative business cases, golden datasets, trajectory tests, retrieval tests, and regression criteria.

  6. 06

    Deploy

    Move the solution into controlled production

    Release the application with the monitoring, documentation, controls, and operational handover needed for ongoing use.

Development framework

Review the capabilities required for production-ready enterprise AI

Identity and permissions

Can the AI access only the information, tools, and actions appropriate to the user and workflow?

Enterprise integration

Can the solution work reliably with the applications and systems involved in the process?

Knowledge and grounding

Can the AI retrieve trusted, relevant, and traceable enterprise information when factual context is required?

Evaluation and quality

Are quality, retrieval performance, agent behavior, and regression criteria defined and measurable?

Operations and observability

Can teams trace AI activity, understand failures, monitor usage, and support the solution after release?

Governance and human oversight

Are guardrails, escalation points, auditability, and human approval requirements built into the workflow?

Which service do you need?

AI consulting, development, or managed services?

AI consulting

Main question

Which AI opportunities should we pursue, and how should we prepare?

Start here if

You need priorities, a business case, or an enterprise AI plan

Typical outcome

Strategy, assessment, architecture, governance, and roadmap

AI development

This service

Main question

How do we design and build the selected AI solution?

Start here if

You have a defined use case ready for implementation

Typical outcome

An AI solution integrated with your workflows and systems

AI managed services

Main question

How do we support and improve AI in production?

Start here if

You already operate AI systems and need ongoing support

Typical outcome

Monitoring, maintenance, optimization, and operational support

Why Intellectyx.ai

Enterprise AI development shaped by production realities

Discuss Your AI Development Project

  • Solutions designed around business workflows

    We start with the process, users, data, systems, and desired outcome rather than forcing a use case onto a particular model.

  • Enterprise integration built into development

    We account for ERP, CRM, operational systems, APIs, knowledge repositories, data platforms, and legacy environments from the start.

  • Evaluation before release

    AI behavior is tested against defined requirements and representative business scenarios rather than relying on demonstration quality.

  • Security and governance considered during engineering

    Permissions, guardrails, traceability, human oversight, and operational controls are incorporated as part of the build.

  • Support beyond deployment

    When the solution is live, our AI Managed Services and AgentOps teams can provide ongoing monitoring, support, and optimization.

Industries

Enterprise AI development for complex industries

We develop AI solutions around the workflows, data, applications, risks, and operational requirements of each industry.

Discuss Your Industry
FAQ

Enterprise AI Development Questions

Enterprise AI development services can include Agentic AI development, Generative AI applications, enterprise knowledge systems, RAG solutions, custom AI software, enterprise integrations, testing, evaluation, and production deployment.
Our primary AI development services include Agentic AI Development Services, Generative AI Development Services, Enterprise Knowledge AI, and Custom AI Development Services. Multiple capabilities can be combined within one enterprise solution.
A focused AI PoC or MVP may take approximately four to eight weeks. A broader custom AI implementation typically takes longer depending on workflow complexity, data readiness, integrations, governance requirements, and approval processes.
Yes. AI solutions can be designed to work with existing ERP, CRM, operational platforms, document systems, data environments, APIs, and other enterprise applications.
We define evaluation criteria around the use case and test the solution using representative business cases, golden datasets, retrieval evaluation, agent trajectory tests, regression checks, and user validation where appropriate.
We take a model-independent approach. Commercial, open-weight, private, and specialized models can be selected based on security, workload, data, performance, deployment, scalability, and cost requirements.
Yes. Stalled Build Recovery assesses an existing implementation, identifies the issues preventing progress, and provides a remediation path. Common areas include integration, evaluation, architecture, data, security, and governance.
Your team can take over operations using the documentation, evaluation assets, and runbooks provided during handover, or Intellectyx can continue supporting the solution through AI Managed Services and AgentOps.

Turn your AI use case into a production-ready solution

Work with Intellectyx.ai to design, build, integrate, evaluate, and deploy enterprise AI around your workflows, data, systems, and operating requirements.

Talk to an AI Development Expert