Data and decision intelligence

Your AI is only as smart as what your data means.

We give AI a shared, governed understanding of your business: a modern data platform, one semantic layer everyone agrees on, an ontology of how your operations connect, and forecasting models that turn it into decisions people act on.

Map your decision backlogTake the data readiness check
The problem

Does our AI understand how our business works?

“Ask three teams for revenue and you get three numbers. Now we want an AI to answer the question.”

  1. Every dashboard defines margin its own way.

  2. ERP, CRM and core systems hold data with no shared meaning.

  3. Monthly reports that explain last month.

  4. Data quality problems discovered in the board pack.

Why a platform

You are right that AI needs better data. You don’t need another two-year programme to get it.

Your teams’ time Run by devx
Product development

TodayEvery dashboard defines margin its own way

With devxOne semantic layer: governed definitions served to BI, notebooks and AI agents alike

TodayERP, CRM and core systems hold data with no shared meaning

With devxAn ontology linking customers, assets, orders, contracts and events, so AI can reason across them

TodayMonthly reports that explain last month

With devxForecasts and alerts refreshed daily, with the drivers shown next to each number

TodayData quality problems discovered in the board pack

With devxData contracts, quality tests and lineage that catch breaks at the source

What we build

Six pieces, what the data means.

Modern Data Platform

One governed home for the data that matters.

A lakehouse sized to your decisions, not to every table you own.

  • BigQuery, Redshift, Databricks or Snowflake with open table formats such as Iceberg
  • Streaming and change-data-capture from ERP, POS, CRM and core banking
  • dbt transformation, orchestration and testing
  • Storage and compute designed for cost
Semantic Layer and Metrics

One definition of revenue, margin and churn.

The business vocabulary, written down once and served everywhere.

  • Governed metric store on dbt Semantic Layer, LookML or Cube
  • Certified datasets for BI and for AI
  • Natural-language questions answered from those definitions
  • Access policies by role and region
Enterprise Ontology and Knowledge Graph

A machine-readable model of how your business works.

The map that lets agents reason across systems instead of inside one.

  • Entity and relationship modelling with your domain experts
  • Graph and vector stores together for GraphRAG
  • Entity resolution across systems of record
  • Ontology APIs that agents call as tools
Forecasting and Predictive Models

Numbers about the future that people trust.

Models built for the decision they inform, with uncertainty shown.

  • Demand, cash flow, workforce and capacity forecasting
  • Churn, propensity, credit and risk scoring
  • Hierarchical and probabilistic forecasts with prediction intervals
  • Time-series foundation models benchmarked against classical methods
Decision Intelligence and Optimisation

From a prediction to the recommended action.

Closing the gap between knowing and doing.

  • Optimisation for pricing, inventory, scheduling and routing
  • Scenario and what-if simulation
  • Decision playbooks that trigger an alert or an agent
  • Feedback loops that check whether a recommendation was followed and whether it worked
Data Governance and Quality

Data you can put in front of a regulator.

Controls that run in the pipeline, not in a policy binder.

  • Data contracts and quality observability
  • Lineage and cataloguing on Dataplex, Lake Formation or Unity Catalog
  • PII classification and masking
  • Retention and consent aligned with India’s DPDP Act and Singapore’s PDPA
How we work

A deliverable at the end of every phase.

  1. Decision discovery · Weeks 1–2

    You get Decision backlog with a value estimate per decision

    Rank your top decisions by value; check data readiness for each.

  2. Foundation sprint · Weeks 2–6

    You get Semantic layer v1 and certified datasets

    Ingest, model and certify only the data the first decisions need.

  3. Models in the loop · Weeks 6–12

    You get Production models with backtest results

    Forecasts and ontology live inside the tools people already use.

  4. Scale · Week 12 onward

    You get Monthly decision scorecard

    New domains, retraining cadence, adoption tracking.

Use cases

Use cases and the outcomes they change.

01 / 10

Demand and supply forecasting

Manufacturing, distribution, consumer goods
What changesProbabilistic forecasts by product and location
Outcome it moves
Forecast accuracy (WAPE)stockoutsworking capital
02 / 10

Cash flow forecasting

CFO office and treasury
What changesDaily rolling 13-week forecast
Outcome it moves
Forecast varianceidle cash
03 / 10

Ask-your-data for leadership

Executive and finance teams
What changesPlain-language questions answered from certified metrics, with the definition cited
Outcome it moves
Time to answerad-hoc requests to analysts
04 / 10

Credit risk early warning

Banks, NBFCs, lenders
What changesSignals from transaction, bureau and behavioural data
Outcome it moves
Warning lead timecredit loss rate
05 / 10

Customer 360 and next best action

Banking, insurance, telecom
What changesOne customer entity plus propensity models
Outcome it moves
Cross-sell ratechurn
06 / 10

Workforce and capacity planning

Contact centres, hospitals, field service
What changesInterval-level demand forecasts feeding rosters
Outcome it moves
Service levelovertime cost
07 / 10

Predictive maintenance

Utilities, logistics fleets, plants
What changesSensor and work-order data combined
Outcome it moves
Unplanned downtimemaintenance cost
08 / 10

Knowledge foundation for agents

Any enterprise rolling out agents
What changesCurated, permission-aware knowledge linked to the ontology
Outcome it moves
Answer accuracygroundedness
09 / 10

Pricing and markdown optimisation

B2B distribution, consumer brands
What changesElasticity models plus an optimiser
Outcome it moves
Gross marginmarkdown spend
10 / 10

Regulatory and management reporting

Financial services, listed companies
What changesLineage-backed, reconciled numbers
Outcome it moves
Days to closemanual reconciliation hours

Our fees move with these numbers.

Every model is backtested against the method you use today before anyone switches.

Questions

Ask us anything.

Ask devx › Questions buyers ask
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h1 · cooper light

Name the three decisions that keep your leadership up at night.

We will show you what data each one needs, what is missing and what a better decision is worth.

Map your decision backlogTake the data readiness check