Data Integration Services
One data layer that
One data layer that
syncs every system
you depend on
Custom data integration built around your schema, not our template. We audit your sources, design the contracts, build the pipelines, and deliver a unified data layer that stays current, accurate, and maintainable.
Pricing signal
Single pipeline from $2,800Full data layer from $14,000Schema audit $800
Submit brief → call within 48 hours → schema brief in 3 days → build starts within 1 week of sign-off
Your team's time investment across a full data integration build is typically 2 to 3 hours per week: one schema review, async feedback on the data contract, and a final quality assurance sign-off on the first live pipeline run. We handle everything else.
Your data is scattered across systems that do not talk to each other
The same customer appears with different values in three different tools. Here is what that looks like, and what it looks like after a data integration build.
Data in silos
Three systems, three different answers
ERP (Dynamics 365)
Customer: Acme CorpInventory: 847 units
Last updated: yesterday 18:32
Shopify Plus
Customer: Acme CorpInventory: 812 units
Last updated: today 06:14 (sync failed at 09:00)
Customer relationship management (Salesforce)
Customer: Acme CorpInventory: unknown
No inventory field mapped. Manual entry required.
Result: your sales team quotes 812, your operations team ships from 847, and your business intelligence dashboard shows nothing. Every decision carries risk.
Live Pipeline Monitor
Your data, unified and observable in real time
Every data integration we build ships with a monitoring layer. This is what the pipeline dashboard looks like 30 days after go-live for a typical 4-source client.
0%
Pipeline health
All systems operational
23,481
records/hour
0
errors today
142
ms avg latency
Data sources
Shopify Plus
active
12,847 rec/hourorders + inventory
Dynamics 365 ERP
active
8,204 rec/hourinventory + pricing
Salesforce customer relationship management
active
2,430 rec/hourcustomers + accounts
Klaviyo
processing
0 errorsevents + segments
Recent pipeline events
Live feed09:14:02OK/sync/inventory → 847 records
09:14:01OK/push/orders → 23 records
09:13:58OK/sync/customers → 12 records
09:13:45OK/events/klaviyo → batch 204
09:13:30OK/sync/inventory → 831 records
09:13:12OK/push/pricing → 2,431 SKUs
Data targets
Business intelligence layerFulfilment (3PL)Marketing automationCustom endpoints
How It Works
Six steps from scattered sources to a single source of truth
Every data integration engagement follows the same schema-first sequence. No build starts before you sign off the data contracts.
1
Schema Audit
Map every source, field, and data type before writing a line of code
Days 1 to 32
Contract Design
Data contracts, field mappings, null rules, and transformation logic documented
Days 4 to 73
Pipeline Build
ETL endpoints built to spec with error handling and retry logic included
Days 8 to 134
Transform and Validate
Transformation rules applied, data quality tests run against real source samples
Days 14 to 175
Go-Live
Production deploy with monitoring configured and rollback scripts pre-staged
Day 186
Expand
30-day hypercare, then add sources or outputs as your stack grows
OngoingCommon scenario
ERP to business intelligence data layer
Pull financial, inventory, and order records from your ERP into a clean analytics layer. Real-time reporting without manual exports.
From $2,800
Common scenario
Multi-channel ecommerce sync
Unify orders, inventory, and customer data across Shopify Plus, Amazon, and custom storefronts into a single operational record. Relevant to application integration too.
From $4,200
Common scenario
Event tracking and customer data platform pipeline
Capture customer behavior events from headless storefronts and route them to Klaviyo, your third-party logistics integration layer, and business intelligence simultaneously.
From $3,600
Client Story
Gameday Gear: data integration that turned email into a revenue channel
How it unfolded
1
Data audit: headless event gaps identified
Customer behavior, product views, and cart events were not reaching Klaviyo reliably. Inconsistent syncing meant segmentation was unreliable.
2
Schema design: custom event taxonomy built
A complete event schema was defined: event names, property structures, and the exact data model Klaviyo needed for reliable segmentation and flows.
3
Pipeline build: custom server-side application programming interface layer
Custom backend application programming interfaces routed events from the headless frontend through a reliable server-side layer, ensuring data integrity regardless of browser conditions.
30 days post go-live: email as a revenue channel
With clean, consistent data flowing into Klaviyo, email flows and campaigns began performing accurately for the first time.
The result
0
.3%of total conversions attributed to email, up from near zero before integration
0
%of email-driven conversions from campaigns, the rest from automated flows
Reliable data layer
Customer segments and flow triggers accurate for the first time since going headless
Architecture
Built on a schema-first foundation
Every pipeline we build follows the same pattern: schema validation at ingress, transformation in transit, quality guards at egress. No data touches a target system without passing all three.
Why Redefine
What most data integration companies skip
Other enterprise integration partners lead with capability lists. We lead with implementation clarity, schema documentation, and pricing you can plan around.
Schema brief before build starts
You receive a full schema brief, including field mappings, transformation rules, and null-handling logic, before a single pipeline endpoint is built. You review and sign off. No surprises mid-build.
Typical partner: starts building immediately
Fixed-price with a go-live date
Single-pipeline data integration projects from $2,800, priced before build, with a confirmed go-live date in the brief. No time-and-materials billing that expands when edge cases appear.
Typical partner: time-and-materials, open-ended
Quality guards designed in, not bolted on
Data drift detection, null-check validation, duplicate detection, and dead-letter queuing are part of the architecture brief. Not added after the first production incident.
Typical partner: reactive error handling only
Common Questions
Data integration consulting: what you need to know
Application programming interface integration connects systems via live endpoints for real-time event exchange. Data integration is broader: it includes ETL pipelines, schema mapping, transformation logic, and building a unified data layer across sources that may not all have REST application programming interfaces. We deliver both. See our application programming interface integration services page for the endpoint-focused build.
Single-source ETL pipelines typically go live in 10 to 14 days from signed brief. Full multi-system data layers with transformation logic and business intelligence connectors run 6 to 10 weeks depending on source system complexity and incoming data quality. Every project starts with a schema audit that produces a realistic timeline before build begins.
Yes. Single-source pipelines start from $2,800 fixed-price. Full data layer builds with 4 or more systems start from $14,000. Schema audits are $800 and credited against any subsequent build. Time-and-materials retainers are also available for ongoing pipeline maintenance and expansion.
Yes. We build flat-file bridges, SFTP-based pipelines, and database-level connectors for legacy systems without a REST or SOAP surface. Feasibility is assessed as part of the free schema audit. In some cases a file-to-application programming interface adapter layer is the most pragmatic route.
Every pipeline includes schema validation at ingress, null-check guards, duplicate detection, and alerting on data drift. Quality rules are defined in the schema brief before build starts. Dead-letter queues ensure failed records are retained and retried, never silently dropped.
Our pipelines are built on async queue architecture with configurable batch sizes and rate limit controls. Load testing at 3x projected peak volume is part of every standard build. For very high volumes, we design partition strategies and horizontal scaling from the start, not as an afterthought.
Is This Right For You?
Is this the right engagement for you?
Not sure? Tell us your situation and we will be straight with you. We turn away projects that do not fit.
Good fit
- You have 2 or more systems that need to share a consistent view of customers, inventory, or orders.
- Your team loses hours each week reconciling data between tools that do not agree.
- You need transformation logic, not just a pass-through connector (custom field mapping, enrichment, deduplication).
- You want your business intelligence or analytics layer to reflect real source-of-truth data, not manual exports.
- Some of your systems are legacy, flat-file based, or lack a modern application programming interface surface.
Not the right fit
- You only need a simple webhook or Zapier-style trigger with no transformation logic.
- Your systems are modern software-as-a-service with native connectors that already handle your use case.
- You want staff augmentation without defined deliverables or a fixed timeline.
- You need a managed integration platform as a service subscription rather than a custom-built pipeline.
Not sure? Tell us your situation and we will be straight with you.
Get Started
Book a discovery workshop
Tell us about your systems and what data needs to flow between them. We respond within 48 hours with a schema audit slot and a preliminary data contract outline.
Call within 48 hours → schema brief in 3 days → build starts within 1 week of sign-off
Brief received
We will review your systems and send a scoped schema brief within 3 business days.
Response within 48 hours
Scoped proposal in 3 days
120+ integration builds delivered
Full code ownership on handoff
Your team's time investment across a full data integration build is typically 2 to 3 hours per week: one schema review, async feedback on the data contract, and a final quality assurance sign-off on the first live pipeline run. We handle everything else.
Ready to unify your data stack?
Most data integration clients go from first conversation to first live pipeline in under three weeks. Start with the schema audit and see what is actually possible.
No commitment. No pitch.