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CASE STUDY
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Middleware that keeps every system
telling one truth.

We build event-driven middleware that syncs your CRM, telephony, billing, e-commerce and ERP in real time, with retries, dead-letter queues and full observability, so a failed sync pages an engineer instead of surfacing as an angry customer three weeks later. Calls log themselves, invoices match deals, and nobody re-keys anything twice.
140+
integrations running in production
99.98%
of events delivered or replayed
4 min
median time to detect a failed sync
System map
event-driven · webhooks
IN SYNC
crmtelephonybillingmiddlewareerpreports
LIVEevents: 212k today · retries: 3 · dead_letter: 0
6
systems connected
<1s
sync latency
0
dropped events
Systems kept in sync by Encloud
VANTAGEmeridianorbitaBLUESUMMITNORTHBRIDGE

Integration failures are quiet.
The damage is not.

Four patterns show up in almost every stack we audit. Each one gets a specific engineering answer, not a plugin.
01SILENT
Syncs fail and nobody finds out for weeks
A webhook endpoint times out, a token expires, a queue backs up, and the first symptom is a customer asking about an invoice that never got created. Without dead-letter queues and alerting, every failure is discovered by accident.
02REKEYING
Your ops team is the middleware
Orders re-typed from Shopify into the CRM, payments copied from Stripe into QuickBooks, call notes pasted by hand. Double entry burns hours daily and guarantees the two systems drift apart anyway.
03SPRAWL
Forty Zaps deep, and nobody owns any of them
Zapier and Make are great until they become the architecture. Undocumented scenarios built by people who left, per-task pricing that climbs with volume, and no retry story when a step fails mid-run.
04CONFLICTS
Two systems both think they are right
The CRM says the customer moved; billing still ships to the old address. Without field-level ownership rules and idempotent writes, every two-way sync eventually creates duplicates and overwrites good data with stale data.

Our fix: integration as owned infrastructure.

Not a folder of Zaps, not a connector marketplace, a small, well-instrumented event pipeline you own, with code in your repo and dashboards your team can read. The same discipline we bring to CRM engineering and AWS work, applied to the seams between your systems.
Map your data flows →
01
Events, not nightly batches
Webhooks and change streams push updates the moment they happen; queues absorb the bursts. A payment in Stripe reaches the CRM in seconds, not at 2 a.m., and the batch jobs that remain are deliberate, not defaults.
Webhook ingestionKafka & Redis queuesSub-second sync
02
Design for failure before the happy path
Every pipeline ships with retries and exponential backoff, a dead-letter queue for what still fails, and idempotency keys so a replayed event never creates a duplicate invoice. Failure handling is the architecture, not an afterthought.
Retries & backoffDead-letter queuesIdempotency keysReplay tooling
03
One owner per field, written down
Before code, we agree which system is authoritative for every synced field, CRM owns the contact, billing owns the balance. Conflict-resolution rules live in a field map both your team and the middleware follow.
Field ownership mapConflict rulesTwo-way sync done right
04
Observability that names the record
Grafana dashboards show throughput, lag and failure rates per pipeline; alerts fire before users notice; every event carries a trace ID so 'why didn't order #4812 sync' is a query, not a forensic project.
Grafana dashboardsPer-record tracingAlerting & SLOs

Integration services, end to end

All engineering services
01
CRM Integration Services
Two-way syncField mappingCustom API appsWebhook handlers
02
Telephony-to-CRM Logging
Auto call loggingScreen pop & contextRecording linksMissed-call workflows
03
Revenue & Billing Sync
Stripe ↔ CRMQuickBooks syncShopify ordersRefunds & disputes
04
Custom Middleware Development
Event-driven designTyped contractsCode in your repoDocker on AWS
05
iPaaS Rescue & Replacement
Scenario inventoryKeep / retire / rebuildTask-cost analysisn8n where it fits
06
Legacy System Bridges
SOAP & file gatewaysERP connectorsChange-data captureStrangler migrations
07
Event & Queue Infrastructure
Kafka topicsDLQ & replayOrdering guaranteesBackfill jobs
08
Sync Monitoring & Reconciliation
Grafana dashboardsLag & failure alertsReconciliation reportsWritten SLAs

How an integration ships at Encloud

Five stages, each with named deliverables. Hover a stage to see what you get.
01
/ 05
Audit
01Map every data flow you have
We inventory every integration, Zap, cron job and manual re-key between your systems, pull the failure history, and rank each flow by business impact, so we fix the sync that loses revenue first.
Integration inventoryFailure-mode reportPriority ranking
02Design the event architecture
One workshop to agree the canonical events, which system owns each field, how conflicts resolve, and what the retry and dead-letter policy is. Every later build decision traces back to this document.
Field ownership mapEvent schemasRetry & DLQ policy
03Build idempotent pipelines
Middleware services in Node.js and TypeScript, developed against sandbox accounts of every connected system, with idempotency keys and contract tests, so a replayed event can never double-charge or duplicate a record.
Middleware servicesIdempotency layerSandbox test harness
04Cut over without dropping an event
Historical data backfilled, old and new pipelines run in parallel with a reconciliation diff until the numbers match, then the legacy Zaps and scripts are retired on a schedule everyone signed.
Backfill scriptsParallel-run diff reportCutover runbook
05Watch it like production, because it is
Grafana dashboards for lag, throughput and failures; alerts routed before users notice; replay tooling your own team can run. Monthly reconciliation proves the systems still agree, in writing.
Grafana dashboardsAlert rules & SLOsReplay tooling

Integration outcomes in spotlight

All case studies
Every call logged to the CRM before the rep hangs up
LogisticsTelephony Integration
VANTAGE
100%of calls auto-logged with recordings
Client portrait
Dispatchers used to log maybe half their calls. Now Dialpad writes every call, note and recording link into Zoho on its own, the coverage argument is over.
Priya Raman
Ops Director, Vantage Freight
Shopify orders and Stripe payments in the CRM in under a second
RetailRevenue Sync
orbita
<1sorder-to-CRM latency, was overnight
Client portrait
Support sees the order, the payment and the refund the moment they happen. We stopped apologizing for yesterday’s data.
Rosa Delgado
Head of Operations, Orbita
QuickBooks and SugarCRM reconciled nightly, automatically
Financial ServicesBilling Integration
BLUESUMMIT
4 hrsmonth-end close, down from 3 days
Client portrait
The reconciliation report lands in my inbox every morning saying the two systems agree. Month-end stopped being a hunt.
James Whitaker
Director of Risk, BlueSummit
58 unowned Zaps retired into one monitored service
B2B SaaSiPaaS Rescue
NORTHBRIDGE
58→1Zaps replaced by owned middleware
Client portrait
We were paying per task for automation nobody could explain. Now it is one codebase, one dashboard, and failures page someone instead of hiding.
Elena Marsh
RevOps Lead, Northbridge
A 2009 ERP now speaks webhooks to the rest of the stack
ManufacturingLegacy Bridge
meridian
0silent sync failures in 14 months
Client portrait
Nobody believed the old ERP could do real-time. The bridge Encloud built has run for over a year without one unnoticed failure.
Daniel Okafor
COO, Meridian Manufacturing

Stop being the human middleware.

A senior integration pod, architect, backend engineer and delivery lead, owns your pipelines from audit through operations. Same people before and after go-live.
38M+
Events processed monthly across client pipelines
99.98%
Delivered or replayed, nothing dropped silently
4 min
Median detection time for a failed sync

The stack between your systems

Your platforms on the edges, our event pipeline in the middle, every piece monitored.
CRM & revenue systems
Telephony & comms
Middleware engineering
Events, queues & observability
iPaaS, when it fits
The systems of record we keep in agreement, field by field.
ZohoZoho
HubSpotHubSpot
SSugarCRM
StripeStripe
QuickBooksQuickBooks
ShopifyShopify

Book an integration audit, not a sales call.

45 minutes with an integration engineer. Bring your list of Zaps, the sync that keeps breaking, or just the spreadsheet your team re-keys every morning, leave with a data-flow map, a ranked failure list, and an honest read on where iPaaS is fine and where you need owned code.
No obligation, no prepared pitch
NDA on request before you share credentials
Keep-what-works verdict on your existing Zaps
You own every line of middleware we write
4.9 / 5average across 140+ integration projects
The audit found nine flows quietly failing that week alone. Six weeks later everything runs through one pipeline with a dashboard I actually check.
Elena Marsh
RevOps Lead, Northbridge
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Frequently asked questions

Weighing custom middleware against another year of Zapier, or against doing nothing? Bring the question to an integration audit and get an answer priced against your own volumes.
Talk to an integration engineer →
Zapier and Make vs custom middleware, when is each the right call?+
iPaaS is right for low-volume, low-stakes flows where a missed run costs nothing, we'll tell you to keep those. Custom middleware wins when volume makes per-task pricing absurd, when a dropped event costs real money, or when you need retries, ordering and conflict resolution that connectors can't express. The audit prices both paths against your actual volumes.
How do you catch failures, and can events be replayed?+
Every pipeline retries with exponential backoff, and anything still failing lands in a dead-letter queue that pages us, median detection is about four minutes, not weeks. Because writes are idempotent, dead-lettered events can be replayed safely after the fix without creating duplicate records or double charges.
Do we actually need real-time sync, or is batch enough?+
Depends on the flow. Call logging, order status and payment events should be real-time, a support rep reading yesterday's data is the whole problem. Ledger reconciliation and reporting extracts are often better as deliberate nightly batches. Most stacks we build are a mix, chosen per flow, not one dogma.
What happens when an API we depend on changes or deprecates a version?+
Each connection sits behind a versioned adapter with contract tests, so a breaking change fails loudly in our test suite instead of silently corrupting your data. We track deprecation calendars for Stripe, Shopify, QuickBooks, Zoho and the rest, and ship adapter updates ahead of provider cutoffs as part of the support plan.
How is our data secured in transit and at rest?+
TLS on every hop, webhook signature verification on every inbound event, credentials in a secrets manager rather than in scenario configs, and queues running inside your own AWS account, your data never routes through a shared multi-tenant automation platform. We scope OAuth grants to the minimum each pipeline needs.
What monitoring and SLAs do we get after launch?+
Grafana dashboards for lag, throughput and failure rates, alert rules routed to us and to your team, and a monthly reconciliation report proving the systems agree. Support runs under a written SLA with named response times, and since the code and dashboards are yours, you can also run it entirely in-house.
What does custom middleware cost compared to our iPaaS bill?+
The audit is fixed-price. A typical first pipeline is a fixed-scope project of four to eight weeks; teams replacing heavy Zapier or Make usage often see the build pay for itself within a year of retired task fees, before counting the hours of re-keying it removes. Ongoing support is a light monthly retainer you can stop anytime.
Can you integrate a legacy or on-prem ERP with no real API?+
Yes, legacy bridges are a core service. We work with whatever the system offers: SOAP endpoints, database change-data capture, even scheduled file drops, and wrap it in a monitored gateway that speaks webhooks to the rest of your stack. The old system keeps running; the rest of your tools stop waiting on it.

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