Aurai STUDIO
Explore AI use cases Light Enterprise AI. Arabic intelligence. Your control.
Intelligence,your enterprise. Connect knowledge. Build agents.
Explore Aurai → Enterprise AI briefing
Opening: introduce Aurai as a studio for teams building enterprise AI. Arabic capabilities and controlled deployment are central themes, not universal performance or compliance guarantees. Aim for 15–20 minutes; the appendix is optional.
Discovery question: Which business process would you most like to improve with AI?
Sources: LDC - Aurai Studio(1).pdf, pp. 5–7, 24–26. Branding and atmosphere extracted from the attached Real Estate and Hospital reference decks.
Aurai STUDIO
Explore AI use cases Light 01 / The opportunity
AI ambition meets enterprise reality. Useful intelligence needscontext, connection,
Which business process would you improve—and what requirements must it meet?
01 Sensitive information needs a defined boundary.
02 Knowledge is scattered across files and systems.
03 Arabic conversations need local context.
04 Business actions need integration and permissions.
05 AI infrastructure adds an operating burden.
Frame these as common discovery themes supported by the platform rationale, not measured findings about this client. Ask the audience to prioritize one constraint.
Discovery question: Where do knowledge gaps, Arabic conversations, or approval delays affect your teams?
Sources: LDC - Aurai Studio(1).pdf, pp. 5–6, 11–14.
Aurai STUDIO
Explore AI use cases Light 02 / Meet Aurai Studio
Your workbench for enterprise AI. A platform to build AI solutions with specialized models, enterprise knowledge, tools, and channels.
Documented capabilities
BUILD Create agents around a business objective.
CONNECT Bring approved data and tools into the workflow.
CONTROL Select deployment, permissions, and oversight.
LDC manages the intelligence layer within the agreed service scope.
Define Large Language Model (LLM) as a model that generates and interprets language. The Studio is a workbench and integration foundation; specific applications require configuration and validation. Do not repeat source claims of day-one value or parity with other models.
Discovery question: Who will own the business outcome, and who will build or operate the solution?
Sources: LDC - Aurai Studio(1).pdf, pp. 5–7, 11, 26.
Aurai STUDIO
Explore AI use cases Light 03 / The Aurai ecosystem
Build the agent. Add focused AI tasks. Select a component to explore its role.
Build Agents — AI Agents Models Language, vision, reasoning Extensions Knowledge, tools, systems Channels Where people interact
Instructions + enterprise knowledge + business rules + permitted actions
Ready-Made Tasks Focused AI functions for applications and workflows
Explore tasks + Application Programming Interfaces (APIs) connect capabilities. An API is not necessarily a task.
Use the prior deck terminology: Models, Extensions, Channels within Build Agents — AI Agents. Ready-Made Tasks complements the agent-building flow. This is an explanatory grouping, not a claim that the Studio UI has this exact layout. API connectivity is a separate integration mechanism.
Discovery question: Do you need a conversational agent, a focused AI task, or both?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 11–14, 19–23; attached previous Aurai decks for terminology. User-confirmed product capability, 15 October 2026: the configured data/knowledge-connected Aurai agent can receive and answer telephone calls. Telephony connectivity and deployment scope require implementation confirmation; no live calling is demonstrated here.
Aurai STUDIO
Explore AI use cases Light 04 / Specialized intelligence
A curated crew of experts. Choose the capabilities the workload needs.
Linguistic expert Modern Standard Arabic, regional dialects, and domain terminology.
Conversations · knowledge · language tasks
Vision & IDP expert Interpret Arabic and English identity, registry, and structured documents.
Intelligent Document Processing (IDP)
Reasoning expert Support reasoning, verification, and controlled tool use.
Rules · analysis · workflow assistance
The primary Studio source describes specialized models and fine-tuning. Exact model choices and performance must be confirmed for the deployment. Do not describe internal reasoning traces or present model cross-validation as a correctness guarantee.
Discovery question: Is the hardest input language, documents, or multi-step reasoning?
Sources: LDC - Aurai Studio(1).pdf, p. 7.
Aurai STUDIO
Explore AI use cases Light 05 / Arabic intelligence
Speak your customer’s language. Arabic capability becomes valuable when it understands the business context.
EGYPTIAN CUSTOMER SERVICE أنا قدّمت الطلب ولسه محدش ردّ عليّا.
MODERN STANDARD ARABIC أرغب في معرفة حالة طلبي.
Illustrative demo Same intent: check a request’s status.
01 Support Arabic and English service journeys.
02 Interpret dialects and formal Arabic in context.
03 Work with bilingual documents and domain terms.
Evaluate the dialects and vocabulary your users actually use.
The examples are fictional editorial demonstrations, not live model outputs. Studio describes Arabic specialization and language/dialect tasks; validate dialect coverage, named entities, mixed scripts, and company terminology against a representative test set. Avoid comparative accuracy claims.
Discovery question: Which dialects, document types, and technical terms must we evaluate?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 19–23.
Aurai STUDIO
Explore AI use cases Light 06 / From conversation to action
An agent connects an answer to a next step. 01 / UNDERSTAND Instructions Purpose, tone, and boundaries
→ 02 / RETRIEVE Knowledge Approved documents and business records
→ 03 / PREPARE Tools & rules Validate the intended next action
→ 04 / PERMIT Act or escalate Execute authorized steps; route exceptions
“What is the policy?”→ “Prepare a request under that policy.”
Illustrative workflow: draft a service request, confirm required fields, then submit through an approved interface.
Explain an agent as configured instructions plus models, knowledge, tools, and controlled actions. Permission checks and review steps shown are proposed implementation controls; business rules and authorized actions are supported building blocks. Human review is required for high-impact decisions.
Discovery question: Which actions may an agent take, and which require human approval?
Sources: LDC - Aurai Studio(1).pdf, pp. 9, 11–18.
Aurai STUDIO
Explore AI use cases Light 07 / Interactive agent builder
Assemble an agent around a purpose. Illustrative demo Arabic service knowledge agent Explain policies, then prepare an authorized service request.
Web portal → Arabic expert → Policy library → API Connector → Human review
Illustrative configuration. No live systems are connected.
Illustrative demo / phone-enabled service agent Incoming call → Agent + connected knowledge → Spoken response → Human review
Illustrative demo / Arabic service knowledge agent Web portal → Arabic expert → Policy library → API Connector → Human review
Alternative building blocks
Vision or reasoning expert · Catalog or authorized records · Database Bridge or Model Context Protocol (MCP) tool · WhatsApp, custom mobile app, or phone calls
The production design must validate model fit, data access, integration scope, and approval rules.
The builder is a presentation simulation, not the Aurai administration UI. Every combination generates a deterministic proposed workflow; it does not configure or invoke a model. Model fit must be validated. MCP means Model Context Protocol, a standard interface for tools and context.
Discovery question: Which knowledge source and application should the first agent connect to?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 11–14, 18. User-confirmed product capability, 15 October 2026: the configured data/knowledge-connected Aurai agent can receive and answer telephone calls. Telephony connectivity and deployment scope require implementation confirmation; no live calling is demonstrated here.
Aurai STUDIO
Explore AI use cases Light 08 / Extensions & enterprise integrations
Bring intelligence to the systems you use. Platform building blocks Knowledge SharePoint, OneDrive, Google Drive; PDFs, Word, text
Databases SQL Server, MySQL, PostgreSQL
APIs & tools API Connector, MCP Client, search, web retrieval
Channels Web, messaging, phone calls, developer APIs
Implementation-specific Connectors still need context. Credentials, permissions, schemas, business rules, and network access must be configured.
Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), ticketing, or enterprise chat may need an approved API or custom integration.
Knowledge, database and tool examples are documented in Studio. Phone-call access is a user-confirmed capability added on 15 October 2026; it is not explicit in the supplied Studio channel list. Confirm the telephony connection and provider data paths. Do not imply a named off-the-shelf connector for every ERP, CRM, hospital system, or enterprise chat platform. Confirm versions, authentication, rate limits, connector availability, commercial channel requirements, and data flows in discovery. External platforms may sit outside the inference boundary.
Discovery question: Which systems have approved interfaces and integration owners?
Sources: LDC - Aurai Studio(1).pdf, pp. 12–14, 15, 18. User-confirmed product capability, 15 October 2026: the configured data/knowledge-connected Aurai agent can receive and answer telephone calls. Telephony connectivity and deployment scope require implementation confirmation; no live calling is demonstrated here.
Aurai STUDIO
Explore AI use cases Light 09 / Enterprise knowledge
Give the answer a source. Retrieval-Augmented Generation (RAG) adds approved context to the answer.
01 / PREPARE Approved files Ingest, split, embed, and index
→ 02 / FIND Retrieve context Semantic and keyword search
→ 03 / GROUND Build the prompt Combine question and relevant passages
→ 04 / RESPOND Answer & review Check support and handle uncertainty
Illustrative demo / employee knowledge Policy v3 · §4
“Which documents do I need for a purchase request?”
Retrieve the current purchasing policy. Cite the relevant section. Ask for missing details.
Studio documents chunking, embeddings, indexing, semantic/hybrid retrieval and prompt templating. Citations, permission-aware retrieval and uncertainty handling shown here are recommended application design requirements to validate, not automatic guarantees of the RAG framework. RAG can improve grounding; it does not eliminate errors.
Discovery question: Which documents are authoritative, current, and accessible to each user?
Sources: LDC - Aurai Studio(1).pdf, pp. 13–14.
Aurai STUDIO
Explore AI use cases Light 10 / Channels & user experience
Meet users where work happens. One agent.Ready to answer calls.
The agent you build can receive and answer phone calls using the same connected data and knowledge base.
Confirm telephony connectivity, access permissions, and the path to a human agent.
Receive and answer inbound calls Web portals Embedded or branded
Messaging WhatsApp · Instagram · Messenger
Mobile apps Developer API integration
Enterprise apps Configured business interfaces
Phone-call access is confirmed by the user in this conversation on 15 October 2026: the same configured agent, connected to data and its knowledge base, can receive and answer telephone calls. The supplied Studio PDF lists web, API and Meta channels but does not explicitly list telephony; retain this provenance distinction. Present inbound answering as a product capability, with the actual telephony connection, call flow, identity checks, language evaluation, connectivity, privacy boundary and human escalation to be scoped. No vendor, protocol, outbound calling, recording, biometric, latency, availability or production-readiness claim is implied. The primary source documents an iframe, a white-labeled web interface, REST APIs, and Meta channels. Mobile means application integration. External telephony or messaging providers may introduce data paths outside the model-hosting boundary.
Discovery question: Where do your users already work and communicate?
Sources: LDC - Aurai Studio(1).pdf, pp. 11–14. User-confirmed product capability, 15 October 2026: the configured data/knowledge-connected Aurai agent can receive and answer telephone calls. Telephony connectivity and deployment scope require implementation confirmation; no live calling is demonstrated here.
Aurai STUDIO
Explore AI use cases Light 11 / Ready-Made Tasks
Focused AI, inside existing workflows. Use a specific function when the business process already exists.
01 Document extraction Turn images and documents into structured fields.
02 Summarization Condense text while preserving key information.
03 Translation & dialect localization Adapt language for the intended audience.
04 Classification Route text or documents into defined categories.
05 Sentiment & emotion analysis Support service-quality and conversation review.
06 Entity extraction Identify names, identifiers, and other data elements.
Inputs, schema, language coverage, limits, and review rules depend on the selected endpoint.
The source describes more than 30 functions but explicitly lists 26 endpoint entries. Avoid an exact marketed count here. Ready-Made Tasks are callable functions; arbitrary APIs and enterprise connectors should not all be renamed tasks. Text and document tasks have distinct input limits and schemas; verify against current API specifications.
Discovery question: Which repeatable task is already part of an existing application?
Sources: LDC - Aurai Studio(1).pdf, pp. 19–23. Discrepancy: marketed function count vs enumerated endpoint list.
Aurai STUDIO
Explore AI use cases Light 12 / Arabic customer service
From frustration to a useful next step. Aurai STUDIO · Customer service Illustrative demo
Start to walk through a fictional Arabic service conversation.
A controlled service journey Understand → retrieve → respond → escalate
Fictional policy and request. No live customer system.
Start Next step → Reset
Illustrative demo / fictional service request
أنا قدّمت الطلب ولسه محدش ردّ عليّا. Customer asks for request status. No private account data is shown.
Retrieve Fictional service policy §2
If a request is delayed, collect the reference through an approved secure flow and route to support.
أقدر أساعدك. هنحتاج رقم الطلب من خلال القناة الآمنة، وبعدها أحوّلك لفريق الدعم. Response acknowledges the issue; a human receives a proposed handoff summary.
All conversation, policy, and handoff data is fictional and deterministic. Present the source-backed service and ticketing patterns; the secure collection flow and approval checks are proposed design choices. No real status lookup, ticket creation, channel API, or model call occurs.
Discovery question: When should a service conversation transfer to a human?
Sources: LDC - Aurai Studio(1).pdf, pp. 11–15, especially customer service and help desk agent references.
Aurai STUDIO
Explore AI use cases Light 13 / Document to workflow
A document becomes a reviewable action. FICTIONAL DOCUMENT / INV-DEMO-042
Nile Sample Supplies فاتورة خدمات تجريبية
Services / خدمات: EGP 2,400Total / الإجمالي: EGP 2,760
Purchase order: missing · Fictional amounts
Illustrative demo Read. Structure. Validate. Review. Walk through a proposed document-processing workflow.
Start Next step → Reset
Illustrative demo / fictional bilingual invoice Supplier: Nile Sample Supplies · INV-DEMO-042 · Total: EGP 2,760 (including EGP 360 tax).
Extract → validate Extract supplier, identifier, currency and total into a defined schema. Check 2,400 + 360 = 2,760. Flag missing purchase-order reference.
Human review → permitted action Reviewer confirms the reference and authorizes a draft ERP entry. This demo sends no data and executes no action.
The invoice and tax amounts are fictional demo data, not a tax interpretation. Document extraction and transfer to business systems are source-supported. Arithmetic checks, purchase-order matching, review gating and draft-only submission are illustrative implementation rules. The browser never creates an ERP record.
Discovery question: Who validates extracted data before it reaches a business system?
Sources: LDC - Aurai Studio(1).pdf, pp. 15, 19, 22.
Aurai STUDIO
← Back to presentation Explore AI use cases Light 14 / Enterprise use-case explorer
Find your next AI use case. SectorAll sectors Banking & Fintech Healthcare Real Estate Construction & Engineering Insurance Oil & Gas Aviation & Travel Retail & Malls Software & Digital Services Enterprise & Shared Services Solution familyAll solutions Arabic customer service Knowledge assistants Document processing IT & employee support Compliance assistance Finance operations Search use cases
Illustrative opportunities 188 use cases · 10 sectors · 6 solution families Clear filters
Banking & Fintech / Arabic customer service Arabic banking service assistant Guide banking service enquiries through chat or inbound phone calls.
Explore variations → Healthcare / Arabic customer service Arabic patient service assistant Explain approved services and administrative preparation steps.
Explore variations → Real Estate / Arabic customer service Arabic property enquiries Match customer requirements with approved property information.
Explore variations → 188 illustrative applications. Explore a tailored mix of workflows across 10 sectors; availability varies by sector and solution family.
Banking & Fintech Account onboarding concierge · Transaction dispute intake
Healthcare Appointment service desk · Claims submission preparation
Real Estate Unit handover concierge · Lease term extraction
Construction & Engineering Material submission checker · Project quality evidence
Insurance Claims status concierge · Renewal enquiry assistant
Oil & Gas Contractor onboarding concierge · Environmental evidence pack
Aviation & Travel Baggage enquiry intake · Refund evidence preparation
Retail & Malls Product catalog intake · Mall facilities requests
Software & Digital Services Release change brief · Security questionnaire assistant
Enterprise & Shared Services Employee onboarding coordinator · Expense claim review
Confirm data access, configured interfaces, and a named human reviewer for each workflow.
Use this catalogue to explore proposed business applications. The header sparkle shortcut opens this slide. If entered from a slide before 15 using that shortcut, Back to slide XX returns to the starting point and next from slide 16 returns there instead of showing slide 17. Normal sequential entry is unchanged. Filter by sector, solution family or keyword, then select Explore variations to continue to slide 16. All catalogue items are illustrative Aurai opportunities, not named customer references or availability commitments. The catalogue is curated by sector rather than a fixed quota. Repeated generic patterns are consolidated under shared services; sector-specific workflows are expanded where distinct. Counts vary by sector and solution family. Each selected case has a source mapping in data/use-cases.json and USE_CASE_RESEARCH.md. Industry references establish application patterns; availability, integrations, certifications and results from other vendors are not Aurai claims. Search normalizes bilingual terms and uses labeled related suggestions when there is no exact match; suggestions retain the selected sector and family. Family counts exclude the search query; unavailable families are disabled. Source-supported agent patterns include customer service, document processing, helpdesk, knowledge, compliance, reconciliation and claims assistance. The reference website inspired industry/process filtering and progressive details only; its product claims, availability labels and roadmap are not transferred to Aurai. Discuss technical fit and qualified human ownership.
Discovery question: Which sector and business process should we explore first?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 11–18, 19–23; attached previous sector decks. Interaction structure reference only: https://auranoxai.com/use-cases/. Industry-pattern references (illustrative designs only): https://learn.microsoft.com/en-us/industry/financial-services/power-platform-copilot-studio; https://adoption.microsoft.com/en-us/scenario-library/financial-services/; https://learn.microsoft.com/en-us/azure/health-bot/overview; https://www.microsoft.com/en-us/ai/use-case/accelerate-claims-administration-with-ai; https://www.microsoft.com/en-us/microsoft-copilot/copilot-101/ai-for-healthcare; https://www.jll.com/en-uk/guides/top-ai-use-cases-for-your-real-estate; https://www.jll.com/en-us/guides/lease-administration-will-save-the-day-for-cre; https://www.yardi.com/blog/commercial-lease-abstraction-software/; https://www.autodesk.com/solutions/aec/construction-ai-software; https://adoption.microsoft.com/en-us/scenario-library/energy-and-resources/; https://www.microsoft.com/en-us/microsoft-cloud/blog/mobility/2024/10/09/ai-solutions-and-data-platforms-for-the-aviation-industry/; https://adoption.microsoft.com/en-us/scenario-library/retail/; https://docs.github.com/en/copilot/tutorials/explore-pull-requests; https://adoption.microsoft.com/en-us/scenario-library/; https://adoption.microsoft.com/en-us/scenario-library/finance/; https://adoption.microsoft.com/en-us/scenario-library/human-resources/.
Aurai STUDIO
← Back to presentation Explore AI use cases Light 15 / Workflow variations
Design the workflow. ← Browse use cases Selected use caseArabic banking service assistant Loan-document intake Compliance evidence assistant Account onboarding concierge Transaction dispute intake Customer verification document pack Trade finance document check Branch product knowledge assistant Relationship meeting brief Merchant integration knowledge Branch IT helpdesk Payment incident handoff Financial crime alert briefing Bank audit evidence organizer Merchant settlement reconciliation Collections case summary Card service navigator Merchant onboarding desk Bank statement extraction Payment instruction intake Guarantee request organizer Treasury document brief Payment investigation dossier Customer review evidence pack Arabic patient service assistant Healthcare document intake Hospital staff knowledge assistant Appointment service desk Referral administration navigator Referral pack organizer Clinical record summary draft Equipment manual assistant Hospital IT helpdesk Hospital maintenance requests Accreditation evidence organizer Patient data request assistant Incident report organizer Claims submission preparation Patient billing query review Diagnostic visit logistics Discharge document pack Patient transport coordination Consent document register Payer query evidence pack Arabic property enquiries Property document assistant Resident service triage Property viewing coordinator Unit handover concierge Lease term extraction Reservation document intake Property due diligence file Sales advisor knowledge Facilities manual assistant Broker CRM support Lease obligation tracker Contract variation review brief Rent invoice reconciliation Installment query assistant Broker lead qualification Resale listing concierge Handover snag-list organizer Service charge query pack Project knowledge assistant Project submission intake Project IT helpdesk Client project enquiry desk Tender clarification intake Information request assistant Project handover knowledge Site report organizer Material submission checker Equipment service handoff Project quality evidence Safety report intake Contract change evidence Subcontractor invoice review Purchase request preparation Project cost variance brief Drawing revision register Tender scope knowledge Progress claim evidence pack Policy service assistant Claims document organizer Claims review assistant Claims status concierge Renewal enquiry assistant Broker product knowledge Underwriting evidence brief Claims procedure knowledge Application pack intake Policy amendment comparison Insurance IT helpdesk Agent portal support Complaint review evidence Premium receipt matching Broker commission review Beneficiary service enquiries Repair estimate organizer Reinsurance correspondence brief Recovery evidence register Operational knowledge assistant Inspection document processing Maintenance request triage Contractor onboarding concierge Maintenance manual assistant Shift record briefing Contractor document checker Field IT helpdesk Safety evidence organizer Permit pack completeness Environmental evidence pack Service invoice comparison Procurement request assistant Equipment datasheet index Maintenance work-pack index Asset history knowledge Arabic passenger service Service disruption triage Baggage enquiry intake Booking change concierge Ground service knowledge Passenger claim pack intake Travel group document intake Service report organizer Airline IT helpdesk Training evidence register Passenger privacy requests Refund evidence preparation Travel agency settlement Special assistance enquiry Passenger feedback routing Agency booking request intake Mall and tenant enquiries Tenant document assistant Supplier invoice intake Order and return concierge Loyalty service assistant Store product knowledge Product catalog intake Tenant onboarding documents Delivery note processing Store IT helpdesk Mall facilities requests Promotion terms review Retail incident organizer Return receipt reconciliation Tenant billing review Store pickup concierge Offer briefing for associates Stock movement reconciliation Arabic product support Engineering knowledge assistant Technical ticket triage Customer onboarding concierge API documentation assistant Release change brief Implementation requirement intake Service order extraction Product feedback organizer Incident handover brief Security questionnaire assistant Software privacy request desk License evidence organizer Subscription record matching Project billing preparation Error-log explanation brief Integration mapping draft Acceptance evidence index Bug reproduction handoff Customer migration questions Employee helpdesk Financial reconciliation assistant Policy review assistant Travel administration concierge Enterprise knowledge assistant Procurement terms knowledge Legal clause knowledge Incoming correspondence triage Meeting action register Employee onboarding coordinator Access request intake Vendor due diligence pack Enterprise audit evidence Supplier invoice assistant Expense claim review Business application helpdesk Budget request completeness Workflow variation Guided answer Assisted draft Approved action
Banking & Fintech / Arabic customer service Illustrative opportunity
Arabic banking service assistant Explain approved service information and escalate uncertainty.
Question Approved context Grounded answer Staff escalation
Data to connect Product terms, service FAQs, authorized request records
System interface Read access to approved knowledge; no write operation.
Human owner & review Customer service team
Verify identity before account access; staff approve account changes.
One opportunity, three workflow variations Examples are illustrative. Select an application in the interactive presentation to tailor its data, systems and review boundary.
01 / Guided answer Retrieve approved knowledge, explain the relevant information and escalate uncertainty. No application write action.
02 / Assisted draft Read source records, extract or check fields, and prepare a draft for a named human reviewer.
03 / Approved action Validate a draft, obtain authorization, call a configured interface within agreed permissions, and record the result.
Implementation boundary Confirm model fit, data access, API scope and audit requirements. Qualified people retain financial, medical, engineering and compliance decisions.
Slide 16 is linked to the catalogue on slide 15. During a shortcut visit from slides 1–14, the header return button goes to the remembered origin; attempting to advance to slide 17 also returns there, preserving the original reveal position. Selecting a use case sets its sector, data, application interface, owner and review boundary. Guided answer, Assisted draft and Approved action are proposed design variations, not separate product editions or guarantees. Approved action is limited to configured, authorized interfaces and human-approved submissions; no financial, clinical, technical or regulatory final decisions are delegated to the demo. All examples are deterministic and execute no backend actions. For real systems, confirm retrieval permissions, authentication, approval enforcement and audit coverage.
Discovery question: Which steps should guide, draft for review, or submit an explicitly approved action?
Sources: LDC - Aurai Studio(1).pdf, pp. 9, 11–18, 24–26. Illustrative application designs based on documented building blocks. Per-case reference mapping: USE_CASE_RESEARCH.md. Industry-pattern references: https://learn.microsoft.com/en-us/industry/financial-services/power-platform-copilot-studio; https://adoption.microsoft.com/en-us/scenario-library/financial-services/; https://learn.microsoft.com/en-us/azure/health-bot/overview; https://www.microsoft.com/en-us/ai/use-case/accelerate-claims-administration-with-ai; https://www.microsoft.com/en-us/microsoft-copilot/copilot-101/ai-for-healthcare; https://www.jll.com/en-uk/guides/top-ai-use-cases-for-your-real-estate; https://www.jll.com/en-us/guides/lease-administration-will-save-the-day-for-cre; https://www.yardi.com/blog/commercial-lease-abstraction-software/; https://www.autodesk.com/solutions/aec/construction-ai-software; https://adoption.microsoft.com/en-us/scenario-library/energy-and-resources/; https://www.microsoft.com/en-us/microsoft-cloud/blog/mobility/2024/10/09/ai-solutions-and-data-platforms-for-the-aviation-industry/; https://adoption.microsoft.com/en-us/scenario-library/retail/; https://docs.github.com/en/copilot/tutorials/explore-pull-requests; https://adoption.microsoft.com/en-us/scenario-library/; https://adoption.microsoft.com/en-us/scenario-library/finance/; https://adoption.microsoft.com/en-us/scenario-library/human-resources/.
Aurai STUDIO
Explore AI use cases Light 16 / Deployment choices
Choose the boundary before the architecture. AI Box Sovereign SaaS Regional Cloud
AI Box — on-premises or LDC hosted Dedicated hardware. Boundary: selected customer site or contracted LDC site. LDC intelligence-layer operations; physical responsibilities differ by location. Air-gapped configurations require local dependencies and a suitable support approach.
Sovereign SaaS Shared in-country platform. Confirm country, tenant controls, backups, connectors, and service scope. Dedicated private-stack option is described for large organizations.
Regional Cloud — confirm availability Described in the older sovereign overview and public website; omitted from Studio. Selected global cloud region with LDC-managed AI layer. No automatic Egypt-only residency.
Confirm storage, processing, backups, telemetry, support access, and external connector paths in the agreed design.
Discrepancy: Studio lists on-premises, private environments and Sovereign SaaS, while the January sovereign overview and website also describe Regional Cloud SaaS. Present the latter as subject to current availability and architecture confirmation. The older AI Box overview uses Family terminology; Studio instead distinguishes single-model and multi-model modes. Prefer Studio. Website blanket offline/no-exfiltration language does not apply to external messaging or tool calls. Country and contractual boundary must be confirmed, not assumed Egypt for all models.
Discovery question: Which data location, isolation, connectivity, and operating model are required?
Sources: LDC - Aurai Studio(1).pdf, pp. 24–26; https://aisolution.linkdatacenter.net/assets/Aurai-Enterprise-Sovereign.pdf, pp. 9–14; https://aisolution.linkdatacenter.net/en/enterprise-ai-solutions/
Aurai STUDIO
Explore AI use cases Light 17 / Security & governance
Control who can access, act, and approve. 01 Identity & access Role-Based Access Control (RBAC) and JWT / OAuth2 authentication are documented.
02 Auditability Audit logs support traceability; confirm coverage, retention, and access.
03 Data boundary Local inference within the selected jurisdiction or physical boundary.
04 Controlled execution Tool gating and structured-output checks help constrain workflows.
05 Oversight by design Propose approval gates, exception queues, and clear human ownership.
06 Deployment validation Verify each application’s data flows and requirements independently.
Infrastructure certifications do not automatically certify an Aurai application or customer deployment.
JWT means JSON Web Token; OAuth2 is an authorization framework. Studio documents access control, logs, authentication, local inference, tool gating and data not used to train global models. Verify contracts and any external service policy. Do not promise zero leakage, absolute compliance, error-free results or automatic certification. Human oversight and approval gates are proposed application design controls. Air-gapped support and updates need an agreed operating procedure.
Discovery question: What permissions, records, and approval steps must the pilot enforce?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 9, 26.
Aurai STUDIO
Explore AI use cases Light 18 / From use case to pilot
Make the first pilot measurable. A proposed journey, with scope and exit criteria agreed together.
01
Choose One workflow, a business owner, and a baseline.
02
Confirm Representative data, permissions, and interfaces.
03
Define Quality, Arabic handling, escalation, and user acceptance.
04
Validate Deployment boundary, operating scope, and approvals.
05
Assess Evaluate results, exceptions, and the case to expand.
Agree how success will be judged before building the workflow.
This is an editorial proposed engagement approach, not a documented delivery promise. No timeline, cost, benchmark or commitment is implied. Suggested criteria should be assessed on representative examples with human scoring and agreed acceptance thresholds.
Discovery question: What evidence would justify moving from a pilot to a wider deployment?
Sources: Proposed discovery framework informed by LDC - Aurai Studio(1).pdf, pp. 11–14, 24–26.
Aurai STUDIO
Explore AI use cases Light 19 / Start with your priority use case
Which workflow Bring the business challenge.
Close with an invitation to scope one use case. Set an owner and a discovery session; avoid delivery commitments. Contact details are configured locally. The contact link opens the official LDC contact page; it does not send a message or book a meeting.
Discovery question: Can we agree one use case, a business owner, and a technical discovery session?
Sources: LDC - Aurai Studio(1).pdf, pp. 5, 11, 24–26; proposed discovery invitation.
Aurai STUDIO
Explore AI use cases Light Appendix A / Orchestration
Three control stages around inference. Pre-model Normalize prompts and dialects; apply caching and initial detectors.
In-model Apply schema constraints, tool gating, and configured cross-validation.
Post-model Validate outputs, apply filters, and use configured reflection or voting.
Heterogeneous routing selects specialist models. Homogeneous instances support load distribution. Neither is an availability or correctness guarantee.
Return to closing ↑
These are documented architectural capabilities. Confirm which are enabled for each model, task and deployment. Source language about zero downtime and guaranteed mathematical soundness is deliberately qualified.
Discovery question: Which detail needs to be validated for this deployment?
Sources: LDC - Aurai Studio(1).pdf, pp. 8–10.
Aurai STUDIO
Explore AI use cases Light Appendix B / Deployment architecture
Define every data path. Selected inference & storage boundary Identity & API Authenticate and authorize
→ Orchestration Route, constrain, and validate
→ Models + RAG Infer and retrieve approved context
External paths to review
Operations to agree
Return to closing ↑
Conceptual architecture, not a network specification. In a suitable air-gapped configuration, required inference, storage, identity and tools must be locally available; external connectors must be removed or replaced. LDC-hosted Box environmental responsibilities differ from on-premises. Confirm network and contractual scope.
Discovery question: Which detail needs to be validated for this deployment?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 12–14, 24–26.
Aurai STUDIO
Explore AI use cases Light Appendix C / Developer integration
Compatible interface. Your selected hosting. Existing compatible client
↓
Configured Aurai endpoint
↓
Authentication + model selection
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Application response
OpenAI-compatible API layer Reuse compatible client patterns and SDKs, subject to endpoint and feature validation.
Interface compatibility does not imply OpenAI hosting, model availability, or a partnership.
Ready-Made Task endpoints are distinct from the compatibility layer. Verify the current API contract.
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An API is an Application Programming Interface. SDK means Software Development Kit. The diagram is conceptual, not runnable sample code. Confirm current base URL, authentication method, supported parameters, streaming behavior and error handling before implementation. Source task endpoint names may contain typographical inconsistencies; consult current specifications.
Discovery question: Which detail needs to be validated for this deployment?
Sources: LDC - Aurai Studio(1).pdf, pp. 7, 19–23.
