Connecting systems so people stop being the integration
API integration connects your website or application to other systems so data moves without someone retyping it. The engineering that matters is not the connection itself but what happens when the other system is slow, down, rate-limited or returns something unexpected.
Integration work looks simple in a demo. Send a request, receive a response, store the result. The difficulty is entirely in the unhappy paths, and those are what separate an integration that runs unattended for years from one that needs someone watching it.
Fragile integrations share a profile. They assume the other system is always available, so a brief outage loses data permanently. They have no retry logic, so one timeout drops an order. They log nothing, so when a record is missing nobody can establish whether it was sent. They handle the documented response shape and break on the undocumented one. And credentials sit in the codebase, where they remain after the developer who added them has left.
When this work makes sense
Questions worth asking any supplier
What happens when the other system is unavailable? Without an answer, data is lost rather than delayed.
Is there a retry strategy, and does it avoid duplicating actions on retry?
Is anything logged? Diagnosing a missing record without logs is guesswork.
Where do credentials live? Keys in a repository outlive the people who added them.
Which system is authoritative when they disagree? Undecided, they will drift apart.
Deliverables
Integration design naming the authoritative system for each piece of data
The integration itself, with error handling as a first-class concern
Retry logic with backoff, and idempotency so a retry cannot duplicate an action
Queuing where the other system is slow or rate-limited
Logging of every exchange, sufficient to answer what happened to a given record
Alerting when failures exceed a threshold rather than on every transient error
Credentials in environment configuration, not in source control
Documentation of what connects to what and what to do when it fails
Built with
Process
Integration work starts by establishing which system holds the truth for each field. Two systems holding customer records will disagree eventually, different addresses, different phone numbers, and without a stated authority the integration will overwrite good data with stale data in whichever direction it happens to run. That decision is made before any code, because it determines the direction of every sync.
The standard nine stages, discovery, strategy, UX/UI, development, content and SEO, testing, launch, measurement and continuous improvement, apply to every project. The paragraph above is what differs for this one.
What moves the number
Pricing depends on scope, functionality, integrations and content requirements. These are the factors that change it most:
Custom integration, an automation platform, or manual process
Automation platform (Zapier, Pabbly)
Fits: Simple, low-volume connections between systems with existing connectors
Limits: Per-task pricing that grows with volume; limited error handling and hard to debug
Custom integration
Fits: High volume, complex mapping, or systems without off-the-shelf connectors
Limits: Build cost and ongoing ownership of the code
Manual process
Fits: Genuinely low volume where automation would cost more than it saves
Limits: Error-prone, does not scale, and the cost is hidden in someone's week
Case studies
No published integration case study. Integration work is inherently client-system-specific and we do not have permission to describe any.
MBGDesk operates from 4 offices in India, United States, United Kingdom, United Arab Emirates. We hold no industry certifications and do not imply otherwise.
Frequently asked questions
Can we use Zapier instead?
For simple, low-volume connections, often yes, and we will say so. It becomes expensive at volume, its error handling is limited, and debugging a failed run is harder than reading your own logs. The crossover point is usually volume plus the cost of a silent failure.
What happens if the other system goes down?
Whatever you designed for. A well-built integration queues the work and retries with backoff, so an outage delays data rather than losing it. Most fragile integrations simply fail the request and move on, which is how records vanish.
Our integration keeps breaking. Why?
Common causes are the third party changing their API without notice, expired credentials, rate limits being hit as volume grew, or error handling that was never written. Logs answer the question quickly, the absence of logs is usually why nobody has answered it.
Can you integrate with a system that has no API?
Sometimes, through scheduled file exchange, email parsing or a database connection. These are more fragile than a proper API and we would say so rather than presenting them as equivalent.
How do we keep two systems in sync both ways?
Carefully, and it is considerably harder than one-way. You need a rule for conflicts, a way to avoid sync loops where each update triggers the other, and a decision about which system wins. Many projects that ask for bidirectional sync are better served by one-way plus a clear authority.
Where should API keys be stored?
In environment configuration, never in the repository. Keys committed to source control persist in history even after removal, and they are one of the most common sources of credential exposure.
How do we test an integration without affecting live data?
Against the provider's sandbox where one exists, which most payment and CRM platforms offer. Where none exists, we build a stub that mimics the responses, including the failure responses, since those are the ones worth testing. Testing only against production is how a developer discovers the retry logic duplicates orders, on real orders.
Services that connect to this
Talk to us about this
Tell us what you are trying to build and we will come back with scope, approach and an estimate.