Data & AI Engineering Company

40+

Pipelines in production

2.1B

Rows processed daily

30+

AI agents running live

99.7%

Pipeline uptime SLA

Why this order matters

An AI agent is only as good as the data feeding it.

Most teams skip straight to the agent. Then it hallucinates, because the data underneath is stale, duplicated, or nobody trusts it. We build the path in the order it has to be built. Foundation first. Agent last.

RAW DATA

Ingest

Pull from every source: apps, APIs, files, legacy databases. Without losing a row.

ENGINEERED

Pipeline

Clean, tested, scheduled. The part nobody sees and everything depends on.

MODELED

Warehouse

One source of truth your team can query. Powers analytics, reporting, and AI with trusted data.

RUNNING

Agents

AI that acts on clean, trusted data. Automates work and delivers answers that hold up in production.

Work that speaks for itself

Three builds, one through-line.

A pure-data rebuild, an agent shipped into production, and one project that ran the whole arc end to end. Every metric says how we got there.

Data Engineering

Turned a failing nightly pipeline into a 90 minute job

A fintech analytics platform rebuilt its data pipeline without downtime. Incremental processing and a redesigned workflow cut costs, reduced alerts, and delivered fresh data before the workday.

↓4× faster pipeline, 60% lower warehouse cost, and ~1 off-hours page per month

Data Engineering

When every team has a different answer

An omnichannel retailer struggled with disconnected data across twelve systems. We unified every source into a centralized analytics platform with automated pipelines and consistent metrics.

↓85% less reporting time, 5× faster dashboards, and one source of truth

Data Quality

The dashboard said revenue dropped 40%

A growing SaaS company couldn’t trust its analytics because broken pipelines and missing records kept slipping through. We added data quality checks and observability across the entire pipeline.

↓90% fewer bad data incidents and issue detection in under 15 minutes

Customer Data Platform

Eleven systems. Zero agreement.

Customer information lived across eleven different systems. We built a unified customer platform that gave every team one consistent view of accounts, revenue, and engagement.

↓11 systems unified into one platform with 95% less manual reconciliation

Six reasons, all verifiable

Not adjectives. Numbers you can check.

99.7%

Pipeline uptime across production jobs. Measured, not promised.

Week 3

First trustworthy dashboard ships in three weeks, not three quarters.

38%

Average warehouse cost cut on the last five optimisation engagements.

Real-time

Agents query live feeds, not nightly exports. So the answers stay current.

Zero lock-in

We build on your cloud and your warehouse. You own the stack when we leave.

30+

Agents running live in client production today. Not in a sandbox.

Data engineering & AI agent development

Two halves of one stack.

The data engineering on the left is what makes the AI on the right reliable. Most agencies do one. We do the path between them.

Data Engineering

Data Pipeline Development

Ingestion, transformation, and scheduling. Built so the on-call engineer can actually read it.

Data Warehouse & Lakehouse

Data warehouse services on Snowflake, BigQuery, and Databricks. One source of truth, modeled properly.

ETL / ELT

dbt-first transformations with tests, so bad data gets caught before it reaches a dashboard.

Real-Time Streaming

Kafka and Kinesis, for the cases where a nightly batch is too slow.

Data Migration

Legacy to cloud, reconciled row by row. No silent data loss.

AI Engineering

AI Agent Development

Agents that act on your data and ship into real production, not demos.

RAG & Knowledge Systems

Retrieval grounded in your warehouse, so answers point back to something real.

MLOps & Model Infrastructure

The deployment, monitoring, and retraining that keep a model working after launch.

Model Integration

Claude, GPT, or open models, wired into your stack and your data.

AI Readiness Audit

Before the agent: is your data ready for one? We give you a straight answer.

the left side is what makes the right side work

The payoff

30+ AI agents. Running live. Right now.

They run because the data underneath them is clean. Most teams hire an AI agent development company and skip that part. We build the pipeline before the agent.

Handles 80% of queries automatically