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Oatey AI Use Case Enablement

project 58a6fd48857532e4

Normalized: oatey ai use case enablement

moreland_contracts

Entity Properties (gold project table)

project_id

58a6fd48857532e4

name

Oatey AI Use Case Enablement

client_id

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canonical_metadata

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created_at

2026-05-02 02:29:59.020102+00:00

updated_at

2026-05-02 02:29:59.020102+00:00

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billable

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recurring

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qa_partner

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lead_dev

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description

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50%

Moderate — a somewhat similar entity exists

100%

Strong source linkage

Source Mappings (2)

	Source	Source ID	Display Name	Confidence	Method	Status
	moreland_contracts	4ef89c9f2300609e1a1325c278098bb7	Oatey AI Use Case Enablement	1.00	fuzzy+embedding	Active
Source Record bronze_moreland_contracts_ma_project_contracts file_hash 4ef89c9f2300609e1a1325c278098bb7 file_name Oatey_AI_Proposal_MorelandConnect_Apr 24 2026V3.docx file_path https://morelandpartners.sharepoint.com/sites/MorelandConnect-BusinessDevelopment/_layouts/15/Doc.aspx?sourcedoc=%7BC52265C5-B9FE-441F-9164-464EC99A5C5D%7D&file=Oatey_AI_Proposal_MorelandConnect_Apr%2024%202026V3.docx&action=default&mobileredirect=true company Oatey Company project_name Oatey AI Use Case Enablement contact_person John Wright contract_type fixed_fee hourly_rate — estimated_hours — total_fee_estimate — brief_project_description Enablement of AI use cases for product intelligence, procurement automation, and data quality monitoring. start_date 2026-04-24 extracted_at 2026-07-01T02:16:43.706626+00:00 raw_text_preview Oatey AI Use Case Enablement Product Intelligence, Procurement Automation, and Data Quality Monitoring Proposal V3.1 — Approach Detail & Run-Rate April 24, 2026 Prepared for John Wright, VP of Analytics Annie Bruder, IT Project Manager Oatey Company Prepared by Paul Franke, Partner · Justin Wray, Partner · David Boone Moreland Connect What's new in V3.1 V3.1 responds directly to the six items John requested at the close of our April 22 working session — concrete architecture, stack, and experience, plus the run-rate economics Oatey takes on once each POC is in production. Changes from V3 → V3.1 Ranked recommendation with Moreland's opinion on sequencing, now up front (Part 2). Fixed-bid investment ranges retained (Part 2 summary table); run-rate costs added per POC. Tech stack made explicit per POC — what Oatey is adopting, in plain terms (Parts 3–5). High-level solution architecture diagram embedded in each POC section. Hero experience mockup for each POC — enough for the council to picture the end user. Representative prior work called out alongside each POC — anonymized, with tech stack and applicability. Part 1 — Strategic Recommendation Oatey's product, customer, and operational data lives across several systems — SAP, Salsify, the public website, spreadsheets, and in the heads of subject matter experts. Each of the three AI Council use cases either consumes or produces data that should feed into that shared layer. Treating the POCs as siloed builds is the failure mode. Each one could deliver narrow value in isolation and then become a disconnected island. Moreland's recommendation is that all three are designed as applications on a shared data layer, with data governance as the connective tissue. That framing does three things: Compounding value. Each completed cross-reference, supplier communication, or anomaly resolution becomes a persistent asset the other POCs and future initiatives can leverage. Sprawl avoidance. Without a shared substrate, each new file_created_at 2026-04-24T13:54:48+00:00 file_modified_at 2026-06-10T18:43:46+00:00 created_by Paul Franke modified_by Paul Franke _dlt_meta —
	moreland_contracts	1e193dd63dc76443cd992bbe1268b2aa	Oatey AI Use Case Enablement	1.00	exact	Active
Source Record bronze_moreland_contracts_ma_project_contracts file_hash 1e193dd63dc76443cd992bbe1268b2aa file_name Oatey_AI_Proposal_MorelandConnect_Procurement Shortage.docx file_path https://morelandpartners.sharepoint.com/sites/MorelandConnect-BusinessDevelopment/_layouts/15/Doc.aspx?sourcedoc=%7BB9DC3D2A-6A85-4B22-965E-FC78701ABC6A%7D&file=Oatey_AI_Proposal_MorelandConnect_Procurement%20Shortage.docx&action=default&mobileredirect=true company Oatey Company project_name Oatey AI Use Case Enablement contact_person John Wright contract_type fixed_fee hourly_rate — estimated_hours — total_fee_estimate — brief_project_description Enablement of AI use cases for product intelligence, procurement automation, and data quality monitoring. start_date 2026-04-24 extracted_at 2026-07-01T02:16:51.092104+00:00 raw_text_preview Oatey AI Use Case Enablement Product Intelligence, Procurement Automation, and Data Quality Monitoring Proposal V3.1 — Approach Detail & Run-Rate April 24, 2026 Prepared for John Wright, VP of Analytics Annie Bruder, IT Project Manager Oatey Company Prepared by Paul Franke, Partner · Justin Wray, Partner · David Boone Moreland Connect What's new in V3.1 V3.1 responds directly to the six items John requested at the close of our April 22 working session — concrete architecture, stack, and experience, plus the run-rate economics Oatey takes on once each POC is in production. Changes from V3 → V3.1 Ranked recommendation with Moreland's opinion on sequencing, now up front (Part 2). Fixed-bid investment ranges retained (Part 2 summary table); run-rate costs added per POC. Tech stack made explicit per POC — what Oatey is adopting, in plain terms (Parts 3–5). High-level solution architecture diagram embedded in each POC section. Hero experience mockup for each POC — enough for the council to picture the end user. Representative prior work called out alongside each POC — anonymized, with tech stack and applicability. Part 1 — Strategic Recommendation Oatey's product, customer, and operational data lives across several systems — SAP, Salsify, the public website, spreadsheets, and in the heads of subject matter experts. Each of the three AI Council use cases either consumes or produces data that should feed into that shared layer. Treating the POCs as siloed builds is the failure mode. Each one could deliver narrow value in isolation and then become a disconnected island. Moreland's recommendation is that all three are designed as applications on a shared data layer, with data governance as the connective tissue. That framing does three things: Compounding value. Each completed cross-reference, supplier communication, or anomaly resolution becomes a persistent asset the other POCs and future initiatives can leverage. Sprawl avoidance. Without a shared substrate, each new file_created_at 2026-06-22T18:07:52+00:00 file_modified_at 2026-06-10T18:43:46+00:00 created_by Paul Franke modified_by Paul Franke _dlt_meta —

Oatey AI Use Case Enablement

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