Service line
AI creates value only when it can use your data, work inside the systems your people already use, and operate under controls your risk and compliance teams accept. Enterprise AI Integration makes all three true.
AI applications
Assistants · Models · Automations
Integration layer
APIs · Events · Connectors
Core systems
ERP · CRM · Documents · Older platforms
Data foundations
Pipelines · Quality tests · Access rules
Governance and controls across every layer
Common challenges
The documents and records a use case needs are scattered, incomplete or have no recorded access rules.
Core systems have no APIs, so AI sits outside the place where the work happens.
Risk, security and compliance teams see an AI system only when it is about to launch.
Business rules live in code that nobody can change safely, so every new use case stalls.
How to get started
Services
The three things every AI use case depends on, whichever service builds it.
Can AI use our data?
Pipelines, quality checks and access controls that make your data usable by AI systems.
Explore Data Foundations for AIWhat we do
You receive
Can AI work inside our systems?
AI connected to your ERP, CRM and core systems through APIs, and the older systems that block it modernized.
First step: Custom Integration Sprint
Explore AI Integration & Legacy ModernizationWhat we do
You receive
Can we trust and defend it?
Policies, risk assessment, security and oversight for every AI system, organized by the NIST AI Risk Management Framework.
First step: Governance Readiness Review
Explore AI Governance & Risk ManagementWhat we do
You receive
Your systems
Choose a system to see how AI connects to it, what it may do there and the controls that apply. Typical patterns; your use cases set the details.
Example use: A policy and procedure assistant
Documents indexed for retrieval, with each one's access rules carried into the index.
Controls
By design
AI gets the minimum access a use case needs, through a service account you control and can revoke.
AI may read and draft freely within its permissions; changes that matter wait for a named person.
Each request, retrieval and change is logged with the user, the system and the reason, so it can be audited.
Deliverables
Across the three services. Each engagement delivers the parts that apply to it.
Questions
No. Most systems can be reached through APIs or events built around them. We modernize only the components that block a use case.
Only through approved interfaces, with the permissions agreed for each use case, and with a person's approval for consequential changes.
Data & Analytics builds data platforms for reporting and forecasting. Data Foundations for AI prepares the specific data an AI use case needs, including documents and access rules, and builds on that platform where it exists.
Your enterprise architect, the owners of the systems involved, and your security, privacy, risk and compliance leads.
Well-defined scopes are delivered as fixed-price engagements; when requirements are still evolving, we provide a dedicated team instead. Either way, the free technical consultation ends with a plan covering tech stack, architecture, timeline and budget, so you know the cost before work starts.
Start with a free technical consultation: a plan covering the right approach, architecture, timeline and budget for your AI work.
Start a project