Your data is scattered across 15+ systems, trapped in silos, and too messy for AI. We build unified data pipelines that extract, transform, and deliver clean, reliable data—making your AI and analytics actually work.
let's be honest about your data situation:
Salesforce, NetSuite, Google Analytics, Stripe, Zendesk, spreadsheets, legacy databases... nobody has a complete view of the business.
Instead of generating insights, your team spends their time downloading exports, copy-pasting between spreadsheets, and cleaning data.
30% duplicate records, inconsistent formats, missing fields, outdated information. Finance, Sales, and Accounting show different revenue numbers.
You've tried ML models and BI dashboards, but can't get clean training data. Projects die in 'pilot purgatory' or show conflicting numbers.
Current State
Plus: Opportunity cost of delayed decisions
With Unified Data Platform
Result: Faster decisions, lower costs, AI-ready
We build production-grade data pipelines that eliminate the chaos:
Pull data from all your sources automatically
Make raw data analytics-ready
All clean data in one unified warehouse
Continuous monitoring and alerting
Unlike DIY with Fivetran/dbt:
Unlike large consultancies:
Unlike managed platforms:
Unified Customer View, Inventory Sync, Marketing Attribution
Deliverable: Technical architecture document, project roadmap, infrastructure setup
Deliverable: Data flowing from priority sources into warehouse
Deliverable: Clean, modeled data ready for analytics
Deliverable: End-to-end pipeline with BI integration
Deliverable: Production data platform with trained team
Typical Investment Range
$50,000 - $150,000
Full project delivery in 4-5 months
5-10 sources vs 20+ systems to connect
GB vs TB, batch vs real-time requirements
Simple joins vs complex business logic and ML features
PII handling, HIPAA, SOC 2, data residency needs
Fivetran and Airbyte are great for extraction (the 'E' in ETL), and we often use them. But they don't solve the hard problems: data modeling (how do you calculate MRR?), quality monitoring (is the data correct?), transformation logic (business rules), and integration with your analytics tools. We build the complete data platform, not just the connectors. We also handle sources these tools don't support and build custom transformations for your specific business logic.
Almost anything. SaaS applications (Salesforce, HubSpot, Shopify, Stripe, etc.), databases (PostgreSQL, MySQL, MongoDB, SQL Server, Oracle), files (CSV, Excel, JSON from SFTP, S3, email), streaming data (Kafka, webhooks, CDC), and even legacy systems like mainframes and on-premise databases behind firewalls. If it has an API or can export data, we can integrate it.
Data quality is built into every layer. During ingestion: Schema validation, freshness checks, row count monitoring. During transformation: Deduplication, standardization, null handling, business rule validation. Post-load: Automated testing, anomaly detection, data profiling. We use Great Expectations and dbt tests to catch issues before they reach dashboards. You get Slack alerts when something's wrong, and dashboards showing data health metrics.
Yes. If you already have Snowflake, BigQuery, Redshift, or another warehouse, we build on top of it. We'll assess your current setup, recommend improvements, and integrate new pipelines alongside existing ones. We can also help migrate from one warehouse to another if needed. Our transformations are portable SQL/dbt, so you're not locked into any vendor.
We support multiple latency tiers. Batch (hourly/daily) for most analytics use cases—simplest and cheapest. Near real-time (5-15 minutes) using streaming ingestion and micro-batching. True real-time (seconds) using Kafka, change data capture (CDC), and streaming transformations. Most clients find that near real-time is sufficient—only a few metrics truly need sub-minute latency. We'll help you determine what's actually needed vs. nice-to-have.
Security is built-in from day one. Infrastructure: Encryption at rest and in transit, VPC isolation, IAM roles with least privilege. Access Control: Role-based access, column-level security for PII, row-level security for multi-tenant data. Audit: Complete logging of who accessed what, data lineage for compliance. Compliance: SOC 2 aligned, HIPAA compliant deployments, GDPR-ready with data locality and deletion. We work within your security requirements and can deploy in your cloud account.
We build for minimal maintenance. Pipelines are self-healing with automatic retries. Schema drift detection catches source changes before they break things. Alerting notifies you only when human intervention is needed. Typical ongoing work: Adding new data sources (we document how, or you can engage us). Updating transformations when business logic changes. Responding to alerts (most are auto-resolved). Most clients manage this with existing team, or we offer retainer support ($5K-15K/month) for hands-off operation.
Once your data is clean, build AI-powered analytics that answer questions in natural language.
Learn MorePower RAG systems with clean, unified data for 90%+ accuracy on domain queries.
Learn MoreAutomate workflows with reliable data triggers and cross-system orchestration.
Learn MoreService Type
Data Engineering
Timeline
4-5 months
Investment
$50K - $150K
ROI Timeline
6-12 months
70%
reduction in data errors
80%
faster analytics delivery
$500K+
annual savings
Schedule a free strategy call to discuss your project and get a custom AI implementation roadmap.
Or email us directly at hello@edgefirm.io. We typically respond within 2 hours during business days.