How it works · Connected, not migrated
Add AI to your existing ERP without migrating a single record
Your ERP already holds years of customers, items, prices and transactions. We put an AI layer on top of it, so agents can read that data, do the repetitive work and propose updates, while a person approves every write.
Why "replace the ERP" is the wrong first move
When a business wants AI, the first proposal is often a new, "AI-native" ERP. On paper that sounds clean. In practice an ERP replacement is one of the riskiest projects a mid-market company can take on: years of master data to cleanse and map, custom reports and integrations to rebuild, every user to retrain, and a cut-over weekend that puts invoicing, purchasing and shipping on the line at the same time.
ERP replacements routinely take longer and cost more than planned, because the hard part is not the software. It is the data, the process changes and the people. And none of that effort automates a single invoice or answers a single question faster on day one.
There is a simpler path. Most of the value people expect from "AI in the ERP" comes from a handful of jobs: matching invoices, answering questions about the data, sorting incoming requests and checking documents. Those jobs can be automated on top of the ERP you already run.
What an AI layer on top of your ERP actually is
An AI layer is a small set of services that sits next to your ERP, not inside it. It has three parts:
- Connectors that read from and write to your ERP and the systems around it: email inboxes, helpdesk, CRM and document storage.
- Agents that do one job each. They read documents, look up records, apply your business rules and prepare the next step.
- An approval queue where a person reviews anything the agent wants to change before it reaches the ERP.
Your ERP stays the system of record. The AI layer never becomes a second database of truth. It reads what it needs, proposes what should change, and writes back only through approved, logged transactions.
How the AI layer reads and writes your ERP data
Every ERP is different, so we choose the connection method in discovery, in this order of preference:
- Official APIs. Most modern and many older ERPs expose REST, SOAP or OData services. These are the safest route for both reading and writing, because the ERP applies its own validation and permissions.
- Database views or a read replica. For reporting and question answering, read-only views or a replica give agents fast access without touching production tables. Writes still go through an official interface.
- File exports and imports. Scheduled exports, EDI or import templates work well for older systems and batch jobs.
- Robotic process automation (RPA). When a legacy ERP has no usable interface, controlled screen automation can enter approved transactions exactly as a user would, with the same permissions and audit trail.
We never write directly into ERP tables. Writes go through the same interfaces your own users and integrations use, so your ERP's rules, number ranges and posting logic still apply.
The architecture, end to end
Here is how one request travels through the layer, whether it is an invoice in the inbox or a question from the finance team:
- ERPSystem of record: customers, items, orders, invoices, ledgers.
- ConnectorAPIs, database views, exports or RPA, with least-privilege access.
- AgentReads, matches, answers and drafts the next step under your rules.
- Approval queueEvery proposed write waits here with its evidence and reasoning.
- UserApproves, edits or rejects. Every decision is logged.
Reads flow from the ERP to the user. Writes flow back from the user to the ERP, only after approval.
Human-in-the-loop approvals on every write
Agents can read freely within the permissions you give them. Anything that changes money, stock, master data or customer records stops at the approval queue. The approver sees what the agent wants to do, the source documents, the checks it ran and anything it was unsure about. One click approves it, edits it or sends it back.
Approval rules follow how your business already works. Low-risk, high-confidence items can be grouped into a daily batch. High-value or unusual items can need a second approver. As accuracy is proven over weeks, you decide whether any category of work can be auto-approved, and you can switch any agent back to read-only at any time.
Every step is written to an audit log: who asked, what the agent read, what it proposed, who approved it and what changed in the ERP. That makes the AI layer easier to audit than the manual process it replaces.
AI for legacy ERP: older systems are welcome
Many of the companies we work with run an ERP that is ten or twenty years old, heavily customized, or hosted on a server in their own building. That is not a blocker. Older ERPs usually have a stable database, and stable databases are easy to read. Where there is no modern API, file imports or RPA handle the write side safely.
Because nothing is migrated, an AI layer is also a low-regret step if you plan to change ERP later. The agents, prompts and business rules carry over. Only the connector changes.
Migrate to a new AI-ERP, or add an AI layer?
| Migrate to a new AI-ERP | Add an AI layer to your ERP | |
|---|---|---|
| Cost | Licenses, implementation partner, data migration, retraining and parallel running | Fixed-price pilot, then a fixed-price production build |
| Time to first value | Months to years, after go-live | 4–6 weeks for a first agent on real data |
| Risk | Business-critical cut-over; data and process risk across every department | One workflow at a time; read-only first; human approval on every write |
| Disruption | New screens and processes for every user | Users keep their ERP; the agent removes manual steps around it |
| Lock-in | Tied to one vendor's AI roadmap | You own the code and can switch AI models or ERPs later |
What you need to get started
- One workflow that costs your team real hours each week, such as invoice entry, reporting questions or ticket sorting.
- A way to reach the data: an API, database read access or regular exports. We confirm this in discovery.
- Someone who owns the workflow and can approve the agent's work during the pilot.
- Your rules on where data may be stored and which AI models are allowed. We deploy on-premise, in a private VPC or in the cloud to match.
Not sure where you stand? The ERP AI Readiness Scorecard takes three minutes and recommends the agents that fit your answers.
Where to go next
See the four agents we deploy on top of existing ERPs, read how we keep ERP data secure, or check fixed-price pilot pricing.
FAQ
Common questions.
Will the AI layer slow down our ERP?
No. Agents read through APIs, read-only views or a replica, and their load is small compared with your users. For heavy reporting we use a replica so production performance is not affected.
Can the AI change data in our ERP without us knowing?
No. Every write goes through the approval queue and is logged with who approved it. Agents only get the permissions they need, and you can switch any agent to read-only at any time.
Our ERP is old and customized. Can you still connect?
Usually yes. Older ERPs often have stable databases that are easy to read, and file imports or controlled RPA can handle writes. We confirm the method during discovery before you commit to a pilot.
What if we change ERP later?
The agents, prompts and business rules are separate from the ERP. Only the connector needs to change, so your investment carries over.
Do we need clean data first?
Not perfectly clean. Agents are often good at spotting duplicates and inconsistent records. We assess data quality during discovery and include clean-up steps where they matter for the pilot.
Works with leading ERPs, CRMs and helpdesks — cloud, hybrid or on-premise.
ERPCRMHelpdeskEmail inboxDocument storageDatabases & data warehousesCloud, hybrid or on-premiseSee an AI agent running on your ERP data in 4–6 weeks.
Fixed scope · fixed price. Human approval on every write. We reply within 1 US business day.