Automation and Integrations
Make your systems share data reliably
When two systems need the same data, we connect them through their APIs so it moves once, correctly, and a person hears about it when something goes wrong.
The problem
The problem this solves
Most businesses use a dozen or more software tools, and each one holds part of the picture. Orders live in one system, inventory in another, customers in a third. Someone copies data between them every day, or a fragile script does it until it quietly stops working.
Integrations fail in predictable ways. An API changes without warning. A token expires. A record arrives with a missing field. The other system is down for maintenance. Rate limits are hit during a busy hour. If the integration was built only for the happy path, data goes missing and nobody notices until a customer complains.
We build API integrations that expect failure. Every call has retries with sensible delays. Records that cannot be processed are kept aside for review rather than dropped. Every run is logged. A named person is alerted when something needs attention. And data formats, usually JSON over a REST API, are validated on the way in and out.
We start by agreeing which system owns each piece of data and what should happen when two systems disagree. That conversation prevents most integration problems before any code is written.
Where a vendor offers a ready-made connector that does the job, we will recommend it. Custom integrations make sense for high volume, complex logic, or systems without good off-the-shelf connectors.
Integrations also need an owner after launch. We document every flow, hand over access to the logs and alerts, and can stay on to maintain them when vendors change their APIs.
Security runs through all of it. Credentials are stored as secrets rather than in code, each connection gets only the access it needs, and sensitive fields are encrypted in transit and at rest. When a staff member leaves or a vendor is replaced, access can be revoked in one place.
What you get
What you get
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Integration design
Data ownership, field mapping, triggers and error rules agreed in writing.
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Dependable connectors
API clients with authentication, pagination, rate limits and retries handled.
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Real-time or scheduled sync
Webhooks for instant updates, or schedules where that is enough.
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Data validation
Incoming and outgoing data checked against rules before it is saved.
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Dead-letter queue
Failed records kept with the reason, ready to fix and replay.
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Run logs
Every sync logged with counts, errors and timing.
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Alerts
The right person notified when failures pass a threshold.
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Runbook
Plain instructions for common problems and how to fix them.
How we build it
How we build it
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1
Study both systems
We read the API docs, test access and look at real data.
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2
Design the flow
Ownership, mapping, triggers and error handling agreed.
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3
Build
Connectors and transforms built with automated tests.
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4
Test with real data
Runs against sandbox or copied data, including bad records.
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5
Launch and monitor
Switched on gradually, with logs and alerts active.
AI and people
Where AI helps, where people decide
AI makes the repetitive parts faster. The decisions that shape your product stay with experienced people.
Where AI speeds things up
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Reading API documentation and drafting client code.
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Proposing field mappings from sample data.
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Generating tests, including malformed records.
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Summarizing logs to find recurring failures.
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Writing the runbook from the finished integration.
Where people decide
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Which system owns each field.
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How conflicts and bad records are handled.
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Whether real-time sync is worth its cost.
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Who is alerted and how fast they respond.
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When the integration replaces manual work.
Is this right for you?
When this is the right choice
A good fit when
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Staff copy data between systems every day.
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An existing integration fails silently or often.
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No ready-made connector covers your needs.
Consider something else when
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A vendor connector or no-code tool already does the job reliably.
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The data moves once a year. A manual export may be fine.
Timeline and cost
What affects the timeline and cost
A single integration between two well-documented APIs usually takes days to a couple of weeks. Complex mappings, poorly documented systems or two-way sync take longer.
We do not publish fixed prices because scope drives cost. How we estimate.
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API quality
Good documentation and sandboxes speed things up; poor ones slow them down.
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Sync direction
Two-way sync needs conflict handling.
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Mapping complexity
Many fields, transforms and rules add work.
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Real-time needs
Webhooks and instant updates cost more than scheduled jobs.
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Volume and limits
High volume needs batching and rate-limit handling.
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Security
Sensitive data needs encryption and restricted access.
Keep exploring
Related services, solutions and reading
Related services
View all related services- Automation and Integrations CRM, payment and API integrations, MCP connections and workflows that stop people copying data by hand.
- API development Well-documented APIs that let your product talk to apps, partners and AI tools reliably.
- Third-party integrations Google Workspace, Microsoft 365, accounting, shipping and marketing tools connected to your own software.
- Database design Data models that stay fast and correct as your business grows, with backups and access rules in place.
- Data migration Move data from an old system to a new one, cleaned, checked and without losing a record.
- Webhooks and event systems Systems that react the moment something happens, such as a payment, a signup or a form, instead of waiting for a nightly job.
Solutions
View all solutions- AI automation and integrations Connect the tools you already use so data moves once, correctly, and AI reads the parts that arrive as text or documents.
- Automated reporting Reports that build themselves from your systems on schedule, with a plain-language summary of what changed.
- Forecasting dashboards Forecast demand from your sales history and seasonality, and flag items to reorder before they run out.
- Price monitoring Collect competitor prices automatically, match them to your products and alert you when something changes.
- Invoice processing Read supplier invoices, match them to orders and push approved ones into accounting, with exceptions flagged for review.
Industries
View all industries- Logistics and transportation Driver apps, order and shipment tracking, document processing and integrations for logistics and delivery companies.
- Ecommerce Online stores, product data cleanup, support assistants, price monitoring and order automation for online retailers.
- Finance and accounting Client portals, document collection, invoice and receipt processing, and reporting for accounting firms and finance teams.
- Property management Tenant portals, maintenance tracking, owner statements and inbox automation for property managers.
Case studies
View all case studies- Facility management platform Every request, inspection and cost for every building now lives in one place, with a clear owner and status.
- Payroll system for an IT services company Payroll is calculated from recorded inputs, reviewed once and sent as payslips in a single batch, with every change logged.
- Beach rental booking system A long-running booking system kept earning while it was extended, tested and given a safe, gradual path to a modern stack.
- Fashion deal aggregator Sale items from more than thirty brands are collected every night and classified consistently by a three-stage pipeline.
Guides and articles
View all guides and articles- How to automate invoice processing Read, check, approve and post supplier invoices automatically, with people handling only the exceptions.
- How to set up automated reporting Replace manual weekly and monthly reports with dashboards and summaries that update themselves.
- How to measure the ROI of AI automation Measure the return on AI automation with a baseline, the right metrics and honest accounting of costs.
MCP servers
View all mcp servers- Developer tools Servers for code hosting, version control, files, containers, error tracking and documentation lookup.
- Automation Servers that connect AI to automation platforms and analytics, so it can trigger workflows and read results.
- AWS The AWS API MCP server from AWS Labs lets AI run AWS CLI commands, suggest commands and plan changes, with read-only and consent modes.
- Azure Microsoft's Azure MCP server lets AI work with many Azure services, from storage and Key Vault to SQL, monitoring and AKS, with a read-only mode.
- Cloudflare Cloudflare's Code Mode MCP server lets AI search Cloudflare docs and the API and execute API calls, within the scopes you grant.
- Coolify Coolify's official MCP server lets AI see self-hosted infrastructure, find unhealthy resources, review deployments and deploy with the right token.
Glossary terms
View all glossary terms- API integration An API integration connects two or more systems through their APIs so data and actions flow between them automatically.
- REST API A REST API is a common style of web API where systems use standard web requests, such as GET and POST, to read and change resources at specific URLs.
- JSON JSON is a simple text format for structured data, made of names and values, that most software and APIs use to exchange information.
- API An API, or application programming interface, is a defined way for one piece of software to request data or actions from another.
- Webhook A webhook is an automatic message one system sends to another's web address when something happens, such as a payment or a new order.
- Database A database is an organized store of data that software can search, update and keep consistent, such as customers, orders or bookings.
FAQ
Questions about API integration
Have a question that is not here? Ask us directly.
A connection that lets two software systems exchange data automatically through their APIs, instead of people copying it. See the glossary entry.
The integration retries, holds records that cannot be sent, and alerts someone if the problem lasts. Nothing is silently lost.
Sometimes, through database access, file exports, email parsing or browser automation. These are more fragile, so we discuss the trade-offs first. See legacy modernization.
For simple, low-volume flows, often yes. Custom integrations make sense for high volume, complex logic or sensitive data. See third-party integrations.