ERP and finance systems
AI that reads and updates orders, invoices and inventory in SAP, Oracle, Microsoft Dynamics or your own ERP.
AI Integration Services
AI that works inside the systems you already run.
We connect AI to your ERP, CRM, core banking, HRMS, ticketing tools, data platforms and your own product through secure APIs, events and connectors. Permissions, audit logs, latency and cost are designed in from the start, so the AI can act on real systems safely.
The problem
Why AI so often stays outside the real work.
01
AI in a separate window
Staff copy data out of one system, paste it into a chat tool and paste the answer back. Errors creep in and usage drops.
02
Permissions ignored
An assistant can read documents or records the user asking could never see in the source system.
03
No record of what happened
When an agent updates a ticket or a customer record, nobody can trace which model, prompt or data led to the change.
04
Slow and costly at scale
An integration that worked in testing slows down and runs up model bills once every team starts calling it.
What we integrate
Secure connections between AI and your systems.
We work with packaged platforms and your own software, and choose the integration pattern that fits each system.
CRM and customer service
Assistants and agents inside Salesforce, HubSpot, Zendesk or Freshdesk, working on live customer and ticket data.
Core banking and HRMS
Careful integrations with core banking, lending and HR systems, where access and audit matter most.
Data platforms
Retrieval and analytics on top of your warehouse or lakehouse, using the same definitions as your reports.
AI in your own product
AI features built into your web or mobile product, with APIs your engineers can own and extend.
Permissions, audit and cost control
Access that follows the user, a log of every AI action, and caching and routing to keep latency and spend in check.
How we deliver
From system map to live integration.
We start with how data and permissions flow today, then design the AI around them.
Always included
- One business metric agreed upfront and reported every week
- A senior squad of two to four people, with a demo every week
- Evaluations, guardrails and security built in from day one
- All code, models and documentation owned by you once invoices are settled
Typical tools
01
Weeks 1 to 2
Map
We map the systems, data, users and permissions involved.
- Systems, APIs and data flows documented
- Permission model and audit needs agreed
- Latency and cost targets set with you
02
Weeks 2 to 3
Design
We choose the integration pattern for each system.
- APIs, events or connectors per system
- Security review of the design
- Fallbacks for when a model or system is down
03
Weeks 3 to 8
Build and test
We build the integrations and test them against real scenarios.
- Connectors with retries and error handling
- Permission and audit checks in every call
- Load, latency and cost testing
04
Ongoing
Release and run
We release in stages and keep watch once it is live.
- Staged rollout with monitoring
- Runbooks for your team
- Option to move to managed AI operations
Where we apply it
Industries we know well.
Further reading
From the blog.
Enterprise AI Agents: How to Build Them for Production
A practitioner's guide to taking enterprise AI agents from demo to production: scope, architecture, guardrails, evaluation, security and rollout.
RAG vs Fine Tuning: How to Choose for Enterprise GenAI
RAG gives a model the right knowledge; fine-tuning changes how it behaves. A clear comparison and decision guide for choosing between them, or using both.
Why AI Projects Fail Between Pilot and Production, and How to Fix It
Most AI pilots stall before production for predictable reasons. Here is how to spot them early and design pilots that are built to ship.
FAQ
Questions we hear a lot.
What are AI integration services?
They are the work of connecting AI models, assistants and agents to the business systems where your data lives and work happens, such as an ERP, CRM, ticketing tool or your own product. Good integration means the AI reads the right data, respects the same permissions as the source system, records what it did and responds fast enough for people to use it.
How do you stop an AI assistant from seeing data a user should not?
We pass the user's identity through to every system the AI calls, so it can only read or change what that person could in the source system. Retrieval indexes carry the same access rules as the documents they come from. We test this explicitly before launch, including attempts to trick the assistant into crossing those lines.
Can AI agents safely update records in our ERP or CRM?
Yes, with the right controls. We limit each agent to the specific actions it needs, add human approval for higher-risk changes, log every action with the data and prompt behind it and make changes reversible where the system allows. We start with read-only or draft actions and widen access as confidence grows.
Do you work with legacy systems that have no modern APIs?
Often. Depending on the system, we use database views, file exports, message queues or a thin API layer built in front of it. We pick the safest option your team can maintain, and we involve whoever owns the system before we touch it.
How do you keep latency and model costs under control?
We set targets for both at the start and test against them. Common tools are caching repeated requests, routing simple tasks to smaller models, trimming the context sent to the model and processing non-urgent work in batches. Costs are tracked per use case so you can see where spend goes.
AI implementation services
Every part of implementation, covered.
AI Readiness Assessment
Use cases ranked, data and systems reviewed, and a costed roadmap in about two weeks.
AI Pilot to Production
One use case taken from proof of concept to a live system people use, in about eight weeks.
AI Adoption and Training
Process redesign, role-based training and an AI usage policy, so people actually use what you build.
Managed AI Operations
AI in production kept accurate, safe and affordable, fully managed or co-managed.
Our services
AI strategy, GenAI and agents, data platforms, analytics, MLOps and transformation.
Talk to a founder about AI Integration Services.
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.