AI does not need to replace your software; it needs to reach it. The value appears when a model can read the record in your CRM, check the order in your ERP, see the thread in your inbox and then act — inside the tools your team already knows, under permissions your security team already understands.
Rather than adding another disconnected tool, we place a reasoning layer between your systems. It reads from each of them, decides what should happen, and writes back through the same permissions a member of staff would have.
Hover or focus any system to see what actually flows across that connection.
AI Layer
One reasoning layer, connected to every system below.
CRM
Contacts, deal stages and activity history move both ways, so the AI works from live pipeline data.
ERP
Orders, stock levels and supplier records are read for context and written back once validated.
Inbound mail is classified and summarised; replies are drafted or sent under your sending domain.
Google Workspace
Docs, Sheets and Drive become both a knowledge source and a destination for generated output.
Microsoft 365
Outlook, Teams, SharePoint and Excel connect through Graph with scoped, auditable permissions.
Slack
Notifications, approval prompts and human handoffs arrive in the channel that owns the process.
Customer conversations run over the Business API with template compliance handled for you.
Calendars
Real availability is checked before anything is offered, and bookings write straight to the owner’s calendar.
Databases
Read replicas and scoped service accounts give the AI facts without giving it write access to everything.
Helpdesk
Tickets are triaged, tagged, answered or escalated, with the full reasoning trail attached.
Payments
Charges, refunds and subscription state are read freely; anything that moves money needs approval.
Custom APIs
Your own REST or GraphQL services, wrapped as tools the AI can call with typed inputs and outputs.
Integration is never the goal in itself. It is the step that turns a capable model into a system that changes an operational number.
This is a starting point rather than a limit. If a system exposes an API, a database, a webhook or even a scheduled export, it can be part of the workflow.
Where pipeline truth lives. Usually the first system an AI layer needs to both read and write.
Orders, stock, invoices and ledgers. Read access is easy; write access is earned through validation.
The channels your customers actually use, plus the queues your team works out of.
Documents, calendars and trackers double as knowledge sources and as destinations for output.
Direct connections for grounding, retrieval and reporting, through scoped service accounts.
Order status, fulfilment and billing state — the data behind most inbound customer questions.
Your own services, plus the glue for anything that predates the concept of an API.
Integration work fails in predictable ways: over-broad credentials, mismatched records, unbounded permissions, duplicate writes and silent breakage. The sequence below exists to close each of those in turn.
We start with the least privilege that makes the workflow possible: a dedicated service account or OAuth app scoped to specific objects and specific actions, never a borrowed admin login. Credentials live in a managed secret store with rotation, not inside a workflow step. Where a vendor only offers all-or-nothing API keys, we put a proxy in front of it so the AI still cannot reach beyond its remit.
Every system models the same business object slightly differently. A “customer” in your ERP is not the same record as a “contact” in your CRM, and your helpdesk probably keys on email address alone. We agree the canonical shape, define the matching keys, handle the messy cases — duplicates, missing identifiers, free-text fields that should have been enums — and document the mapping so nobody has to reverse-engineer it later.
The AI inherits rules, not a blank cheque. Actions are split into three tiers: free to perform, allowed with logging, and requiring explicit human approval. Anything that moves money, contacts a named client, deletes a record or changes a contract sits in the third tier by default. Field-level permissions stop sensitive data reaching the model at all, and role-based rules mean the assistant cannot surface a record the requesting user could not open themselves.
Then we decide how data actually moves. Webhooks and event streams where the source system supports them, polling on a sensible interval where it does not, and batch reconciliation overnight to catch whatever both missed. Writes are idempotent, so a retry cannot create a duplicate record, and conflicts resolve against a declared system of record rather than whichever update happened to arrive last.
Integrations do not fail loudly. Tokens expire, rate limits tighten, a field gets renamed, a schema changes on a Friday. We instrument every connection with health checks, failure alerts, latency and volume dashboards, and a dead-letter queue that holds failed records instead of dropping them. When something breaks you find out from an alert, not from a customer.
Most integration disagreements are really a disagreement about which of these three you are buying. Choosing deliberately saves months.
The AI reads from your systems and produces answers, summaries or briefs, but never writes back. Nothing in your source data can be corrupted by the integration, which makes it the fastest path to production and the easiest to get security sign-off for.
When to use it
Use when you want value quickly, the data is sensitive, or the organisation is not yet comfortable letting AI change records.
What it costs you
Trade-off: a person still has to act on the output, so it saves thinking time rather than handling time.
Records stay aligned across two or more systems. The AI reads context, takes a decision and writes the result back — a CRM stage change, an updated ticket, an ERP record. This is where duplicate data entry actually disappears.
When to use it
Use when the same information is being maintained by hand in more than one place and the copies keep diverging.
What it costs you
Trade-off: needs a declared system of record, idempotent writes and conflict rules, so it takes longer to design properly.
A business event — a form submitted, a payment failed, a deal moved, a document received — triggers a workflow that runs to completion on its own. Nothing is polled, nothing waits for a person to notice, and the response happens in seconds.
When to use it
Use when the delay between something happening and someone reacting to it is itself the cost.
What it costs you
Trade-off: requires webhook support or a reliable change-detection strategy, and disciplined retry and replay handling.
These are the five questions that decide whether an integration gets approved. Answered the way we would answer them on a call with your security lead.
No, and we prefer not to have it. What we need is a dedicated service account or OAuth application scoped to the specific objects and actions the workflow uses — for example, read on contacts and deals, write on deal stage only. Your IT or operations team creates it, holds it, and can revoke it at any time without breaking anything else. Admin credentials are occasionally required for the initial app registration on platforms like Microsoft 365 or Salesforce; in those cases someone on your side performs the consent step while we walk them through it, and we never hold the admin credential ourselves.
Send us your stack — CRM, ERP, inbox, helpdesk, databases, the spreadsheet nobody admits to. We will map what can be connected, what it unlocks, and what it would take to build.
Integration map and access plan included · No obligation