Most stalled AI projects aren't AI problems — they're data problems discovered in week six instead of week one. We audit, build, and monitor the ingestion, warehouse, and quality-gate layer that makes every other AI initiative possible.
Ingestion, schema contracts, quality gates, and monitoring — the full layer that makes AI systems trustworthy downstream.
Every source system profiled for volume, structure, and the specific quality issues that would break downstream AI — scored before any pipeline is built.
Change-data-capture or interval-scheduled pipelines with schema contracts enforced at ingestion, replacing manual exports.
A single source of truth AI and BI systems both query — the same number means the same thing everywhere.
Business-rule and schema validation catching bad data before it reaches downstream systems, not after.
Live dashboards so a broken feed is caught in minutes and a cost creep is caught before the invoice.
The pipeline topology and a real ingestion pattern — not a diagram of generic “data flow.”
// elhaa Ingestion Pipeline — Schema-Contracted Job const job = await elhaaPipeline.run({ source: 'salesforce.opportunities', mode: 'cdc', schema: OpportunitySchema, qualityGate: 'great-expectations:v2', onValidationFail: 'quarantine', alertOn: 'failure' });
A real monitoring surface, not a promise — freshness, quality, and cost per source, visible at a glance.
Inventory, sales, and customer data lived across twelve spreadsheets and three disconnected systems — no AI initiative could get off the ground because nobody trusted a single number, and the finance and ops teams routinely reported different revenue figures for the same week.
We audited every source, built CDC ingestion pipelines with schema contracts into a single warehouse, layered in automated data-quality gates, and stood up monitoring so a broken feed is caught in minutes rather than discovered at month-end.
*Illustrative example based on a representative engagement.
Every source system profiled for volume, structure, drift, and the specific quality issues that would break downstream AI.
Warehouse or lake design sized to real volume and access patterns, with schema contracts defined per source.
Ingestion pipelines stood up with automated data-quality gates, and historical data backfilled with full validation.
Freshness, quality, and cost dashboards live from day one, with documentation your team can operate without us.
Scheduled jobs completing successfully, tracked and alerted like any other production system.
Share of records passing schema and business-rule checks before reaching downstream systems.
How quickly new data becomes queryable after it's created upstream — per source, not averaged.
Warehouse and pipeline costs tracked weekly against a forecast, with alerts before overruns.
Because most stalled AI projects aren't AI problems — they're data problems discovered too late. We'd rather surface that in a week-one audit than watch a pilot fail in month three.
No — we typically work alongside a data team that's stretched thin, or stand up the first version of this for a team that doesn't have one yet. Full handover, including runbooks, is standard.
Most business reporting and RAG use cases are well served by scheduled batch or CDC on a short interval. True streaming (sub-second) is a real but much rarer requirement — the source audit tells us honestly which one your use case needs, rather than defaulting to the more expensive option.
Yes. We design the warehouse layer to serve both AI systems and existing BI/reporting tools through the same governed models, so you're not building two parallel data stacks.
A focused first pipeline (one or two source systems) typically ships in 3–6 weeks; a full warehouse migration is scoped separately based on volume and source count.
That's the normal starting point, not a blocker. The audit quantifies exactly how messy, and prioritises cleanup where it actually affects the AI use case you care about — not everything at once.
A 30-minute call. We'll tell you honestly whether this is the right solution — and what it would take.
A short form, then a 30-minute call. We reply within one working day.
We'll be in touch within one working day.