Enterprise Data Platform
A lakehouse on AWS with SAP Datasphere and BW as governed sources, engineered by the team that already knows your SAP data.
Data & AI practice
Where SAP heritage meets applied AI.
Enterprise data platforms, document AI, GenAI copilots and applied industry AI: engineered on AWS, grounded in the SAP data we've been running for 13+ years.
Enterprises don't need another vendor promising GenAI. They need someone who can land the data foundation, get documents into structured records, ground copilots against source-of-truth, and ship the applied products that show a return. That's what Phoenix runs: AWS as the platform, SAP as the data heritage, and a track record of moving customers from PoC decks to production.
- Storage footprint reduction on SAP archiving programmes
- 70%+
- Storage footprint reduction on SAP archiving programmes
- Live products in production: Smart OCR and EstateEdge
- 2
- Live products in production: Smart OCR and EstateEdge
- First for RAG, agents and enterprise copilots
- Bedrock
- First for RAG, agents and enterprise copilots
- Advanced Tier partner, MAP-eligible for migrations
- AWS
- Advanced Tier partner, MAP-eligible for migrations
Four services. One Data & AI practice.
AWS-first data and AI built on 13+ years of SAP-data context. The frontier we invest in, with proof already live: a lakehouse practice with 70%+ archiving lifts, Smart OCR in AWS Marketplace, an AI real-estate product in production.
Document AI · Smart OCR
Arabic and English extraction from IDs, invoices, contracts and handwriting: structured JSON in S3, feeding Bedrock knowledge bases. Deployed, live on AWS Marketplace.
GenAI, RAG & Agents
RAG knowledge bases and enterprise copilots on Amazon Bedrock; SAP Joule enablement where the data lives in SAP.
Applied & Industry AI
Industry-tuned AI products: pricing intelligence (EstateEdge, retail price-compare) and logistics AI for routing, fleet and driver performance.
AI put to work, across function and industry.
A cross-section of what Phoenix has shipped under the Data & AI practice. Each one lives on the customer's own AWS estate, integrated with the systems that already run the business.
Bid intelligence
Tender documents to ranked opportunities in minutes. Conversational AI reads incoming tender packs, extracts requirements, flags risks and produces evaluation memos.
HR AI assistant
Onboarding, recruitment and policy queries under one agent, grounded in HR policy and integrated with the HRIS.
Marketing intelligence
Streaming intake of competitor listings, campaigns and market signals; automated content drafts and campaign insight for fast-moving verticals.
Executive report generation
Raw operational data to narrative strategic reports: scheduled generation of analyst-grade reports in minutes, with citations back to source data.
RAG-based furniture design
Industry-tuned generative AI over the customer's own design corpus: reference-augmented ideation with production-ready outputs.
Phoenix MCP
Model Context Protocol layer connecting the customer's CRM (and adjacent systems) to frontier-model surfaces. Copilots read authoritative live data instead of stale exports.
What's already in production.
- Smart OCR: live in AWS Marketplace. Arabic and English extraction into structured JSON in S3, deployed on customer AWS accounts.
- EstateEdge: pricing intelligence in production. An AWS-native real-estate pricing product used by developers and brokers across the region.
- SAP archiving & migration: 70%+ footprint cuts. Historic data moved to Amazon S3 tiered storage, hot data kept in HANA, same-application UX.
Frequently asked
Is Phoenix's Data & AI practice AWS-only?
AWS is the platform of record: Bedrock for GenAI, S3/Redshift for the lakehouse, Marketplace for productized solutions. Where the workload sits in SAP, SAP Joule is enabled directly. Non-AWS clouds are supported case-by-case where a customer standard requires it.
How does the SAP heritage matter for a Data & AI engagement?
Most data foundations fail on messy source integration. Thirteen years of running SAP end-to-end means Phoenix reads S/4HANA, BW and Datasphere as first-class sources: extractions arrive clean, semantics are preserved, and downstream ML models train against data the business actually trusts.
What's actually in production today?
Smart OCR: a document-AI product live on AWS Marketplace, extracting Arabic and English into structured JSON. EstateEdge: an AWS-native real-estate pricing product used by developers and brokers. SAP archiving programmes that have cut storage footprints by 70%+.
Can you build a RAG copilot on top of our existing document estate?
Yes, that's the common pattern. Smart OCR ingests the corpus into structured JSON in S3, Bedrock Knowledge Bases wrap it with retrieval, and a copilot layer sits on top with guardrails, citations and access control. Grounded, not hallucinated.
How do you commercialise applied-AI products like EstateEdge?
Each applied-AI product is deployed as a tuned instance per customer: same core engine, customer-specific data ingestion, KPIs and interfaces. Sold via subscription against a named business KPI, not licence fees.
The earliest conversations are usually the most useful.
Whether you're scoping an SAP move to cloud, restarting a stalled programme, or just trying to figure out where data and AI fit, start with a conversation.
