AI-Ready Data Platforms

Pipelines and warehouses agents can read.

Twistag designs, builds and runs the data platform that reports, teams and AI agents read from every day: clean, current and connected to the ERP and CRM, in the company’s own cloud.

Book a call See what it delivers

A dense network of industrial pipes, valves and gauges

Why a data platform

Most AI stalls on data: spread across systems, out of date and owned by no one.

01Three versions of the same number. Finance, sales and operations each report their own.
02Yesterday’s data for today’s decisions. Exports and manual refreshes set the pace.
03Agents with nothing reliable to read. Pilots work on samples, then fail on the real thing.

What gets built

One platform for reports, teams and agents.

Every source is ranked by what fixing it is worth before anything is built, and every data product reports against a number agreed with leadership.

01Source mapEvery source ranked by what fixing it is worth.
02Ingestion pipelinesBatch and streaming feeds from the ERP, CRM and other systems.
03Warehouse and modelsSnowflake, BigQuery, Databricks or Redshift, modelled with dbt.
04Quality checksTests for freshness, completeness and duplicates on every run.
05AI-ready layerVector search and APIs agents can read, with permissions.
06Ownership and runbooksAn owner for every pipeline and a runbook for every failure.

Example pipeline runToday 06:00

From source systems to the agent layer

ERPOrders ingested48,210 rows2 min
CRMAccounts ingested9,412 rows1 min
QualityChecks on every table3 duplicate customers held for review40 s
WarehouseModels rebuilt112 models, all tests passed6 min
Agent layerSearch index refreshedReady for agents and reports1 min

5 stages, all logged3 rows held for review

How it runs

Six to twelve weeks to the first data product.

Discovery fixes the scope first. The platform grows once the number agreed with leadership has moved.

Sources to connect

6 weeks

Source audit and value mapWhat each source is worth

Ingestion pipelinesBatch and streaming feeds

Warehouse and modelsModelled and tested

Quality checksFreshness, completeness, duplicates

AI-ready layerSearch and APIs for agents

First data product liveMeasured against the agreed number

A data ownerDecides definitions and priorities.

Access to the source systemsOr exports while access is set up.

One number leadership wants to trustThe first data product is built around it.

After the first data product

Govern it, build on it or hand it over.

Data Strategy & GovernanceGovern the data

Definitions, owners, access and lineage across every domain.

Next step Multi-agent Systems & Agent EngineeringPut agents on top

Agents that read current, trusted data and act on it.

Next step

Full handoverRun it in-house

Infrastructure as code, pipelines and runbooks handed over in full.

Related work

Data platforms already at work.

All case studies

Datatalks · Sports and media50+sports organisationsUnifying fan data across 50+ sports organisationsRead the case

Defined.ai · Software & platforms250K+contributorsScaling AI training data collection to 250K+ contributorsRead the case

Questions

About AI-ready data platforms.

What does it cost?

Cost follows scope: the systems to connect, how mature the current data layer is and how long the team stays. A proposal follows within a week of the first call.

How soon can work start?

A thirty-minute call, a written proposal within seven days, and a discovery sprint of two to four weeks to confirm scope before the build.

Which clouds and warehouses does Twistag use?

AWS, Google Cloud and Microsoft Azure; Snowflake, BigQuery, Databricks and Redshift. Twistag extends what is already in place before adding anything new.

Does the company need a data platform before starting with AI?

No. Data preparation comes first wherever it is needed and is scoped as part of the plan.

Who owns what is built?

The client owns everything: source code, infrastructure as code, pipelines, models and documentation, handed over in full with training for the team.

Can the internal team run it afterwards?

Yes. Engineers pair during the build, every system is documented, and handover walkthroughs happen before the engagement ends.

Other Data & Cloud services.

Data & Cloud overview

Data Strategy & GovernanceQuality, lineage and access, defined onceExplore Cloud Migration & DevOpsInfrastructure that scales without downtimeExplore System IntegrationCore systems connected into one operationExplore

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Tell us about the company and what it needs. A senior lead takes it from there.

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