Service · Integration and automation
Systems integration and business process automation
We connect ERP, CRM, accounting, sales and support channels with the discipline of a production system: every record is processed once, whatever fails is retried, and someone gets alerted. That's how the lead platform we run for law firms works, with AI in production and its cost measured every month.
Proof · A lead platform for law firms, with AI in production
An integration that fails silently is worse than none at all
Most automations are built for the happy path: the data arrives, gets copied, done. In production the data arrives twice, arrives incomplete, arrives while the other system is down, or changes format on a Tuesday. If nothing catches it, the error shows up weeks later in the books or in a customer who never got an answer.
That's why we treat every integration as production software: each record is processed once even if it arrives twice, whatever fails is retried and logged, there are automated tests and alerts, and someone knows what to do when they go off. That's the difference between an automation and a system you can depend on.
What we build
- 01
Integrations between systems
ERP, CRM, accounting software, online stores and payment gateways connected through APIs, with a log of every record that comes in and goes out.
- 02
Fault-tolerant data flows
Processing that doesn't duplicate even when a record arrives twice, retry queues, an archive of everything received so it can be replayed, and alerts when something doesn't add up.
- 03
Lead capture and routing
Calls, forms, chats and messaging flowing into one system, with duplicate detection and the information each team needs, in its format.
- 04
AI in production
Transcription, document data extraction and classification with language models, with cost caps, rule-based validation and human review where a mistake is expensive.
- 05
Monitoring and monthly support
Operations dashboards, backups and adjustments when your systems or your process change.
Everything ships with automated tests, automated deployment and documentation: your team can maintain it without depending on us.
Risks we control
- Duplicate records
- Every event is processed exactly once, even when it arrives twice.
- Silent failures
- A retry queue, an archive of what came in so it can be replayed, and alerts with a clear procedure.
- A vendor changing its API
- Monitoring on every integration and automated tests against what each API promises.
- Runaway AI costs
- A per-use cost cap, rules before the model, and spend reported every month.
What we build it with
Integrations in TypeScript or Python, with queues and retries on PostgreSQL or Redis, and no-code tools only as transport when that makes sense. We connect by API to whatever you already use: HubSpot, Salesforce, QuickBooks, Google Workspace and the like.
How we take an integration to production
01
Map the flows
In the technical review
Which data moves between which systems, how often per month, where it's copied by hand and where it gets lost. With two starting numbers: hours and errors.
02
Build for production
In phases
We start with the flow that costs the most and finish it, with retries, tests and alerts, before moving to the next.
03
Measure and sustain
After a month, and beyond
We compare against the starting numbers and leave the system with monitoring and monthly support.
Is it right for your company?
It's for you if…
- Your operation depends on data that today moves between systems by hand.
- You tried no-code automations and they break silently as volume grows.
- You want to use AI with cost and accuracy figures, not because it's trendy.
It may not be for you if…
- You want a template chatbot or an afternoon automation: no-code tools will do it for less.
- You expect AI to decide on its own in payments, reconciliations or inventory: there the model proposes and a person or a rule decides.
Frequently asked questions
How is this different from a no-code automation?
No-code tools are great to start and for low volumes. When the process becomes critical, what matters is what you don't see: a duplicate record isn't processed twice, whatever fails is retried and logged, and there are tests and alerts. Our lead platform for law firms started exactly like that: the logic moved from a no-code flow that was failing silently into a service of its own that doesn't lose or duplicate records, and the no-code tool stayed on only as the messenger.
Which systems do you integrate with?
Any that expose an API or allow importing and exporting data: ERP, CRM, accounting software, online stores, payment gateways, telephony and messaging. In the technical review we check what each one allows before promising anything.
Where do you use AI, and where not?
The model extracts and proposes; rules validate and execute. We use it to read messy input such as calls, PDF invoices or emails, and not to decide alone where a 2% error would mean reviewing 100%. Every use has a cost cap and a measured accuracy figure.
What happens after delivery?
The system keeps running with alerts and backups. We offer monthly support and monitoring to adjust it when your systems or process change; if you'd rather your team maintains it, we hand over the code, the tests and the documentation.
What happens to the personal data flowing through the integrations?
It stays in accounts in your company's name. We never use it to train AI models, we define how long it's kept, and we give you the list of third-party services that process it.
Go deeper
Tell us which flow is costing you the most
In 30 minutes we review it and tell you how we'd solve it and which numbers we'd measure before and after.