Data integration 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
Submit brief → call within 48 hours → schema brief in 3 days → build starts within 1 week of sign-off
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.
Three systems, three different answers
Result: your sales team quotes 812, your operations team ships from 847, and your business intelligence dashboard shows nothing. Every decision carries risk.
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.
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.
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.
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.
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.
Gameday Gear: data integration that turned email into a revenue channel
Customer behavior, product views, and cart events were not reaching Klaviyo reliably. Inconsistent syncing meant segmentation was unreliable.
A complete event schema was defined: event names, property structures, and the exact data model Klaviyo needed for reliable segmentation and flows.
Custom backend application programming interfaces routed events from the headless frontend through a reliable server-side layer, ensuring data integrity regardless of browser conditions.
With clean, consistent data flowing into Klaviyo, email flows and campaigns began performing accurately for the first time.
of total conversions attributed to email, up from near zero before integration
of email-driven conversions from campaigns, the rest from automated flows
Customer segments and flow triggers accurate for the first time since going headless
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.
What most data integration company partners 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.
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.
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.
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 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.
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.
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.