Predictive Analytics for
Confident Decisions.

Move beyond “forecast spreadsheets.” We engineer production predictive systems—time-series forecasting, anomaly detection, and scenario planning—built on governed data foundations with auditability, observability, and decision-grade reliability.

Request Scoping

Forecasting + Scenarios

Governed Data Products

Audit Trails + Monitoring

Predictive Systems Trusted in Operational Environments

8-15%
Forecast Error Reduction

Backtested + monitored models, not spreadsheets.

2-6wk
Time-to-First Model

Foundation pipelines + reusable patterns.

24/7
Monitoring + Drift Alerts

Data quality + model health in production.

$0.
Vendor Lock-In

Own features, models, and serving artifacts.

Beyond the Forecast Demo.
Decisions, Not Charts.

Most predictive initiatives fail because data is brittle, assumptions are untracked, and models degrade quietly. We build systems with data contracts, backtesting, and observability—so decisions remain reliable on Day 2.

The Analytics Failure Pattern

What most “build teams” ship:

  • Brittle Data Inputs

    Schema drift, missing signals, and silent pipeline breaks.

  • No Backtesting Discipline

    Forecasts look good in slides, not against reality.

  • Zero Decision Integration

    Outputs don’t connect to planning, ops, or automation.

The Coretus Predictive Standard

Decision-grade predictive systems:

  • Governed Data + Contracts

    Data quality gates, lineage, and versioned datasets for stable features.

  • Backtesting + Scenario Planning

    Time-series evaluation, benchmarks, and scenario tooling for trust.

  • Monitoring + Decision Integration

    Drift alerts, audit trails, and integration into workflows + systems.

Less Guesswork. More Governed Decisions.

Strategic Capabilities.

Moving from Data to Decisions.

Time-Series Forecasting

Demand, capacity, revenue, and throughput forecasting with backtesting + scenario overlays.

  • Benchmarks + Baselines
  • Scenario Controls

Data Products + Contracts

Reliable datasets, lineage, quality gates, and versioning for stable feature delivery.

  • Data Quality Gates
  • Lineage + Ownership

Anomaly + Early Warning

Detect drift, breakdowns, and operational anomalies with alerts and triage workflows.

  • Multi-Signal Detection
  • Alert Routing

Optimization + Planning

Translate predictions into actions: reorder points, staffing, routing, and constraints.

  • Constraints Modeling
  • What-If Planning

MLOps + Serving

Automated training, model registry, CI/CD, and predictable deployment patterns.

  • Model Registry
  • Repeatable Deploys

Governance + Auditability

Decision logs, reproducible runs, and policy-friendly controls for enterprise trust.

  • Audit Trails
  • Role-Based Access
/// Predictive Stack

Hardened Pipeline for
Decision Intelligence.

Data Contracts + QA

Input Integrity

Versioned datasets, quality checks, and schema contracts so features stay stable in production.

Schema + Contract Gates
Freshness + Completeness
Lineage + Ownership
ContractsQALineage

Feature + Time Index

Reproducibility

Point-in-time correctness, feature definitions, and consistent time alignment for clean training/serving parity.

Point-in-Time Correctness
Feature Definitions
Train/Serve Parity
FeaturesTimeParity

Backtesting + Scenarios

Trust

Rolling evaluations, benchmark baselines, and scenario tools so stakeholders trust outputs in real planning cycles.

Rolling Backtests
Benchmarks + Baselines
Scenario Overlays
BacktestsBenchmarksScenarios

Monitoring + Retraining

Ops

Drift detection, alerting, performance tracking, and retraining triggers so the system stays accurate over time.

Data Drift Alerts
Model Health Metrics
Retraining Triggers
MetricsAlertsLoops
/// Predictive Accelerator

Ship Predictive.
Skip the Chaos.

We deploy the Coretus Predictive Kernel™—a pre-hardened foundation for data contracts, feature/time correctness, backtesting, and monitoring.

Your teams focus on use-case impact and decision integration, not rebuilding the stack.

6-10 Wk

Delivery Cycle Saved

1 Stack

Unified Predictive Ops

Built for audit trails, monitoring, and decision integration.
Kernel Hardened

Your Decision Reality

Demand • Supply • Risk • Operations

Coretus Predictive Kernel v3.1

Contracts

  • • QA
  • • Lineage

Features

  • • Time
  • • Parity

Backtests

  • • Bench
  • • Scenarios

Monitoring

  • • Drift
  • • Alerts
/// Pre-Configured Predictive Pods

Deploy Production-Ready Predictive Squads.

Integrated delivery units specialized in data contracts, forecasting, and predictive ops—so you ship reliably, not repeatedly rework.

Forecasting Architect

Designs forecasting + scenario systems: evaluation, baselines, time alignment, and decision outputs.

ForecastingBacktestingScenarios

Data Products Lead

Builds data contracts, QA gates, lineage, and reliable features that survive schema drift.

ContractsLineageQuality Gates
≤8%
MAPE Target Band
Backtesting + Monitoring Included

Squads arrive with data contracts, evaluation harnesses, and drift monitoring hooks—built-in from day one.

MLOps & Serving Engineer

CI/CD, model registry, scheduled training, and stable serving patterns for predictable deployments.

RegistryCI/CDServing

Predictive Ops Lead

Monitoring, drift detection, alert triage, and decision instrumentation for operational confidence.

DriftAlertsDecision Logs
/// Architectural Integrity

The Predictive Blueprint.

Predictive systems are a pipeline: ingest, validate, feature, predict, and monitor—built to survive operational change.

01. Ingest + Validate

Reliable pipelines, data contracts, and quality gates for stable inputs.

Tech Stack:
Contracts • Quality Gates • Lineage

02. Feature + Time Index

Point-in-time correctness and consistent time alignment across signals.

Tech Stack:
PIT • Parity • Time Align

03. Forecast + Scenarios

Backtested models with scenarios and benchmarks for decision-grade reliability.

Tech Stack:
Backtests • Benchmarks • Scenarios
Decision Grade

04. Serve + Monitor

Serving, alerts, drift signals, decision logs, and retraining triggers.

Tech Stack:
Metrics • Alerts • Audit Logs
Governed Outputs
Data Contracts
Audit Trails
/// Delivery Framework

The Road to Reliable Predictions.

A phased model that prevents brittle analytics: data, evaluation, deployment, then scale.

Phase 01

Decision + Data Audit

Define decision points, data contracts, success metrics, and baseline benchmarks.

Output: Predictive Feasibility Blueprint
Phase 02

Feature + Evaluation Harness

Build point-in-time features, baselines, rolling backtests, and scenario evaluation.

Output: Decision-Grade Model Baseline
Phase 03

Deploy + Monitor

Ship serving, alerts, drift monitoring, and audit trails—wired into workflows.

Output: Production Predictive Stack
Phase 04

Operate, Improve, Scale

Iterate with monitoring signals, retraining triggers, and expanded decision coverage.

Output: Measurable Decision Impact
/// Performance Validation

Proven Predictive Outcomes.

Analytics Case Archives
12%
Stockouts Reduced

Forecasting for
Retail Replenishment

Planning drifted due to manual overrides and inconsistent inputs across regions.

Shipped backtested forecasting with data contracts, scenarios, and monitoring.

"We stopped debating which number to trust—backtests and monitoring made it decision-grade."

RP
Replenishment Lead
Retail Ops
3.1x
Faster Detection

Anomaly Detection for
Production Lines

Failures were found late due to no early-warning signals across sensor streams.

Deployed multi-signal anomaly detection with alert routing and audit logs.

"Alerts became actionable. We could trace what changed, when, and why the model fired."

OP
Ops Manager
Manufacturing
/// Delivery Models

Predictive Partnership Models.

Choose the engagement aligned with decision velocity, data reliability, and operational ownership.

Fast Deployment

Managed Predictive Squads

Embedded team specialized in data contracts, forecasting systems, monitoring, and decision integration.

Velocity & Reliability
SQUAD SPECS
Strategic Advisory

Fractional AI CTO

Define predictive roadmap, data contracts, evaluation standards, and governance for production trust.

Strategy & Architecture
EXPLORE ADVISORY
Build-Operate-Transfer

Build-Operate-Transfer

We incubate your predictive platform, operate it in production, then transfer ownership to your teams.

Platform Ownership
VIEW BOT MODEL
Scale Delivery

Predictive ODC

Your dedicated predictive analytics delivery center for continuous improvement and cross-domain rollouts.

Operational Scale
EXPLORE ODC
/// Trust & Controls

Governed
Predictive Decisions.

Predictive systems must balance speed with error control. We embed governance, monitoring, and auditability so decisions are trustworthy in production.

Backtesting + Benchmarks

Rolling evaluations and baselines before outputs are used in planning.

Controlled Access + Lineage

Role-based access, lineage, and reproducible runs for enterprise compliance.

Audit Trails + Drift Monitoring

Decision logs, data drift alerts, and retraining triggers with traceability.

Audit Logs

Traceable Runs

Contracts

Quality Gates

HITL

Review Gates

Monitoring

Drift Alerts

/// Analytics Briefing

See the Predictive Stack.

A 100-second breakdown of data contracts, backtesting, monitoring, and decision integration.

Coretus Predictive Analytics Briefing
Analytics Lead
Principal Engineer
Predictive Systems Lead
01:40 • DECISION MODE

Forecasting

Backtested models + scenarios.

Data Contracts

Stable, governed inputs.

Monitoring

Drift alerts + audit trails.

/// Predictive FAQs

Frequently Asked
Predictive Specs.

Service Identity
Predictive Analytics & Data

Data Quality & Contracts?

Yes. We design contracts, QA gates, lineage, and ownership so production signals stay stable.

Backtesting & Benchmarks?

We build rolling evaluations, baselines, and scenario overlays so stakeholders trust the outputs.

Monitoring & Drift Alerts?

Telemetry, drift detection, and audit logs are built-in—so regressions don’t surprise ops.

Decision Integration?

We connect outputs to planning workflows, thresholds, and systems—not just dashboards.

Multiple Models, One Standard?

Yes. We standardize feature/time correctness, evaluation, and monitoring across use cases.

Predictive Feasibility?

We can deliver a 48-hour feasibility audit for your highest-impact forecasting or anomaly workflow.

Request Analytics Briefing

Own Your Decision Intelligence.

Stop shipping dashboards that don’t change outcomes. We build production predictive systems—forecasting, anomaly detection, and scenario planning—on governed data foundations with measurable decision impact and 100% IP sovereignty.

Time-Series + Scenario Engine

Governance + Audit Trails

100% Model & Feature Ownership

Request Analytics BriefingRequest Analytics Briefing