Keystone AI

Optimize supply chain decisions and automate production planning with a scientific AI engine designed for manufacturers to reduce inventory and forecast error.

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About Keystone AI

Keystone AI’s Deep Enterprise™ is a scientific decision engine built to address the planning crisis currently facing global manufacturing and CPG industries. It moves beyond traditional, fragile forecasting methods by embedding AI into the core operating models of complex organizations. The platform focuses on transforming how enterprises manage inventory, production, and labor by replacing manual intuition with data-driven automation, specifically targeting the inefficiencies that lead to rising inventory costs and SKU proliferation. The system works by first converting standard ERP transaction data into fine-grained, AI-ready event streams. This prevents the need for costly rip-and-replace ERP transitions. Once the data is unified, the Foundation Forecasting™ module generates probabilistic, multi-horizon forecasts that quantify uncertainty instead of relying on single-point estimates. These predictions are then fed into specialized agents, such as the Deep Inventory Control Agent and Production Planning Agent, which automate high-volume tactical decisions like safety stock levels and SKU-level production management. Designed for large-scale manufacturers, pharmaceutical companies, and consumer packaged goods firms, the platform serves supply chain planners, operations leads, and finance executives. It is particularly effective for organizations struggling with volatile demand and the compound errors associated with manual model overrides. By providing a single source of truth across regions and departments, it helps teams move from manual tactical loops to high-level strategic oversight, ensuring that planning and execution are tightly aligned. What sets Keystone AI apart is its lineage and scientific rigor. Incubated within the Keystone advisory firm and led by a team including former chief economists from Amazon and Microsoft, the platform applies advanced management science to enterprise logistics. Unlike generic BI tools, it offers a specific system of record for forecasts that accounts for lumpy orders and global disruptions. This ensures that inventory remains productive and aligned with actual market behavior rather than sitting still as a cost center.

Pros & cons

Pros

Integrates with existing ERP systems without requiring a rip-and-replace approach.
Quantifies uncertainty with probabilistic forecasting rather than relying on point estimates.
Automates high-volume tactical decisions like SKU-level production and replenishment.
Led by a highly experienced team from companies like Amazon, Microsoft, and Moderna.
Supports multi-horizon planning across enterprise, regional, and SKU levels.

Cons

Requires high-volume, high-velocity granular data to function effectively.
Pricing is not publicly disclosed and requires a custom consultation.
Focused strictly on large enterprise manufacturing and logistics use cases.
Implementation likely requires internal data team alignment to set up event streams.

Use cases

Supply chain planners at CPG companies can automate safety stock calculations and inventory positioning to reduce capital tied up in finished goods.
Manufacturing operations leads can use production planning agents to manage SKU-level schedules, reducing manual overrides and improving quality predictions.
Finance executives in the pharmaceutical industry can align annual plans with regional forecasts using a single source of truth to manage market volatility.
Distribution managers can automate fulfillment and order response loops, allowing their teams to move from tactical execution to strategic oversight.

Features

labor and capacity planning
unified timeline event streams
automated safety stock management
sku-level production planning
deep inventory control agents
probabilistic multi-horizon forecasts
foundation forecasting™
erp data transformation

Pricing

Enterprise

Price varies

Foundation Forecasting™
Deep Inventory Control Agent
Production Planning Agent
Replenishment Policy Agent
ERP data stream integration
Probabilistic demand forecasting
SKU-level planning
Multi-horizon outputs

FAQs

What data sources can Keystone AI ingest?

The platform is designed to ingest high-volume, granular transaction data directly from existing ERP systems without requiring a full system replacement. It transforms these records into fine-grained event streams that include orders, shipments, and invoices.

How does Foundation Forecasting differ from traditional methods?

Unlike traditional point forecasts that provide a single number, this tool produces probabilistic, multi-horizon outputs that quantify uncertainty. This allows planners to see a range of possibilities and make more resilient decisions during volatile market conditions.

Does this tool replace my existing ERP?

No, the platform is built to work alongside your current ERP rather than replace it. It organizes your existing transaction data into scientific event streams, adding a layer of intelligent decision-making and automation on top of your current infrastructure.

What industries is the Deep Enterprise platform built for?

The platform is specifically tailored for manufacturers, consumer packaged goods (CPG) companies, and the pharmaceutical industry. Its agents are designed to handle the specific complexities of SKU proliferation, production planning, and global distribution.

What kind of tactical decisions can the AI agents automate?

The platform includes specialized agents for SKU-level production planning, inventory positioning, safety stock management, and fulfillment order response. These agents handle high-volume tactical loops, allowing human planners to focus on strategy.

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Keystone AI

ERP Data Specialist (Contract)

engineering hybrid Bellevue, US$100,000 - $200,000 contract

Education Requirements:

Bachelor’s, Master's degree or PhD in Technology or related technical field
Bachelor’s degree in Information Systems, Business, or a related field

Experience Requirements:

4+ years of experience working with ERP systems, with strong hands-on SAP experience
Deep hands-on experience with SAP ECC and/or S/4HANA
Experience supporting or mapping data across systems such as Oracle, Microsoft Dynamics, NetSuite
Strong SQL and data modeling experience
Comfort working with data engineers, writing specifications, and validating outputs

Other Requirements:

Candidates must be authorized to work in the U.S. without sponsorship
Strong communication skills and ability to work cross-functionally
Experience with AI platforms, Large Language Models, Generative AI, Cloud AI
An understanding of cloud services: compute, storage, accelerated computing
Knowledge of master data domains (Customer, Vendor, Material, Finance)

Responsibilities:

Act as Keystone.ai’s expert on SAP and ERP data structures
Define mapping logic between raw ERP tables and our scientific data model
Partner with product and data engineers to build ingestion templates and transformation logic
Create schema reference guides, field usage dictionaries, and normalization logic
Ensure that our platform supports customer-specific schema variants

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