AI projects fail more often from missing or low-quality data than from missing models. NKKTech builds the data foundation AI needs: pipelines that don't break silently, warehouses that scale past 10TB, semantic layers your analysts can trust, and observability that alerts when an upstream changes. dbt-first, warehouse-agnostic, with the same engineering rigor we ship for AI itself.
Modern data stacks that survive scale. Six capabilities every project ships with.
Fivetran, Airbyte, or custom connectors for sources we own (rare). Pipelines monitored, alerted on freshness violations, versioned in Git.
Bronze → Silver → Gold layered architecture. Tests on every model. Documentation auto-generated. Lineage exportable to data catalogs.
Kafka, Kinesis, or Pub/Sub for high-velocity sources. Materialize or ClickHouse for real-time aggregations. CDC patterns for transactional databases.
Great Expectations or dbt tests on every Gold table. SLA tracking on freshness, completeness, uniqueness. Alerts wired to PagerDuty or Slack.
dbt Semantic Layer or Cube.dev. Metrics defined once, consumed by BI tools, AI agents, and reverse-ETL — guaranteed consistent across surfaces.
Census or Hightouch to push enriched data back to operational tools (Salesforce, HubSpot, Customer.io). Closes the loop from warehouse to action.
1–2 weeks. Audit current pipelines and warehouse, identify gaps, prioritize for AI readiness.
3–5 weeks. Lift critical pipelines, set up warehouse and dbt project, ship Bronze + first Silver models.
2–4 weeks. Gold layer (the metrics analysts and AI agents consume), test coverage, alerting.
1–2 weeks. Documentation, runbooks, dbt training for your team, on-call rotation handoff.
Event-stream warehousing (Segment/Rudder → warehouse), cohort modeling, retention dashboards, churn prediction features for AI agents.
Unified ledger from multiple sources, regulatory reporting pipelines (SOC 2, GDPR ROPA), real-time fraud features.
Order + clickstream + ad-spend unified, lifetime-value modeling, attribution, AI-ready feature store for recommendations.
Supply + demand metrics, match-quality scoring, liquidity dashboards, pricing-optimization features.
Sensor-stream warehousing, OEE calculation, predictive-maintenance features, supply-chain visibility.
HIPAA-compliant warehouses, de-identification pipelines, longitudinal cohort building, research-ready datasets.
Because the model is rarely the bottleneck. 80% of AI project effort is data engineering: getting the right data, clean enough, fresh enough, with the right access controls. Skip this work and your AI features either ship slow, ship wrong, or never ship.
Snowflake for most B2B SaaS clients (best ecosystem). BigQuery for clients already in GCP. Databricks when ML+SQL workloads need to share a platform. ClickHouse for high-volume cost-sensitive analytics. Honest tradeoffs — we don't force-fit our preferred stack.
USD 40K–100K for a standard 8–14 week build, depending on number of sources and existing infrastructure. Ongoing warehouse + tool costs typically $1K–$10K/month for mid-market scale.
Yes. We work alongside in-house teams, train them on dbt and the deployed stack, and hand off ownership. About 60% of our engagements are augmentation, not full replacement.
Tests on every dbt model (not just the Gold tables). Freshness alerts wired to PagerDuty. Anomaly detection on key metrics (Monte Carlo or custom). Documented SLA for each table consumed downstream. The default is 'fail loud' — better to alert and reprocess than to serve silently bad data.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Tony's team understood our legacy PHP system faster than our internal team. Zero downtime migration, exactly as promised. The bilingual PM made communication seamless.
We went from 15 hours/week of manual prospecting to fully automated lead gen in 8 weeks. ROI in 60 days as Tony promised.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Last updated: · Reviewed quarterly for accuracy.
30-minute free discovery call with a senior NKKTech engineer (not a sales rep). We'll review your requirements, scope an engagement, and tell you honestly whether we're the right fit.
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