Study guide
22.3 Context Grounding: Retrieval-Augmented Generation with Company Data
UiPath Automation Developer Professional UiPath-ADPv1
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1 Chapter 1: Exam Overview & Blueprint Map
1.1 About the UiPath-ADPv1 Exam: Format, Fees & Policies 1.2 The Exam Topics Mapped to This Guide & a Study Plan
2 Chapter 2: REFramework Architecture & State Dynamics
2.1 State Machine Architecture & The Four Core States 2.2 Configuration Management: Settings, Constants, and Assets 2.3 Transaction Types & The Dispatcher vs. Performer Architecture 2.4 Adapting REFramework: Tabular Data, Collections & Linear Processes
3 Chapter 3: REFramework Exception Handling & Recovery
3.1 BusinessRuleException vs. System.Exception Handling Patterns 3.2 Retry Mechanisms: Queue Retries vs. REFramework MaxRetryNumber 3.3 Consecutive System Exceptions & Graceful Process Termination
4 Chapter 4: State Machines, Custom Log Fields & REFramework Testing
4.1 Building State Machine Projects in Studio 4.2 Logging Levels, Robot Logs & Custom Log Fields in REFramework 4.3 Testing a REFramework Project With and Without Orchestrator Queues
5 Chapter 5: LINQ Queries & DataTable Operations
5.1 LINQ Essentials for Collections & Filtering 5.2 Advanced DataTable Querying with LINQ 5.3 In-Memory DataTable Transformations & Column Operations
6 Chapter 6: Regex, DateTime, JSON & Invoke Activities
6.1 Regular Expressions & Text Parsing for Automation 6.2 DateTime Formatting, Timezone Conversions & TimeSpan Calculations 6.3 JSON Parsing, JSONPath & Serialization with Newtonsoft.Json 6.4 Invoke Method & Invoke Code Activities 6.5 Data Referencing in Invokes: DataTable, List & Dictionary Arguments
7 Chapter 7: Modern UI Automation & Unified Targeting
7.1 Modern Design Experience & The Unified Target Concept 7.2 Anchors, Relative Elements & UI Automation Activities 7.3 Dynamic Selectors, Variables & Wildcards in Selectors
8 Chapter 8: Object Repository, Computer Vision & Remote Runtime
8.1 Object Repository & UI Descriptor Libraries 8.2 AI Computer Vision for Unattended & Remote Interfaces 8.3 Automation in Virtual Environments & UiPath Remote Runtime
9 Chapter 9: Advanced UI Automation: Browser Modes, Agentic UI & macOS
9.1 Browser Automation with the WebDriver Protocol 9.2 Agentic UI Automation: ScreenPlay, Semantic Activities & Healing Agent 9.3 macOS Automation: Native Apps, Office Apps & AppleScript
10 Chapter 10: Advanced Control Flow & Exception Architecture
10.1 Flowcharts, Sequences & Parallel Control Flow Patterns 10.2 Global Exception Handler Architecture & ErrorAction Directives 10.3 TryCatch, Retry Scope & Custom Exception Architectures
11 Chapter 11: Orchestrator Queues & Transaction Management
11.1 Queue Architecture, SpecificContent & Transaction Lifecycles 11.2 Queue Items SLA, Postpone, Deadlines & Priority Scheduling 11.3 Bulk Operations, Transaction Status Updates & Queue Triggers
12 Chapter 12: Orchestrator Tenant & Folder Entities
12.1 Asset Types, Per-Robot Assets & External Credential Stores 12.2 Modern Folder Hierarchy, User/Robot Assignment & Permissions 12.3 Storage Buckets, Webhooks & Environment Promotion 12.4 Orchestrator Tags: Labels, Properties & Governance
13 Chapter 13: Unattended Execution, API Triggers & Cloud Robots
13.1 Unattended Job Execution: Folders, Priorities, Background vs. Foreground & Runtimes 13.2 API Triggers: Starting Jobs from External Systems over HTTP 13.3 Serverless and Cloud VM Robots: Cloud-Hosted Execution Options
14 Chapter 14: Monitoring, Recording & Solutions Management
14.1 Orchestrator Monitoring, Trigger Alerts & Job Health 14.2 Job and Transaction Recording: Troubleshooting Faulted Unattended Jobs 14.3 Solutions Management: Packaging and Deploying Automations with Their Resources
15 Chapter 15: Debugging, Remote Debugging & Profiling
15.1 Studio Debugging Tools: Breakpoints, Panels & Execution Control 15.2 Remote Debugging: Remote Machine and Unattended Robot Connections 15.3 Profile Execution: Finding Performance Bottlenecks in Studio
16 Chapter 16: RPA Testing & Test Suite
16.1 UiPath Test Suite Overview, Test Cases & Given-When-Then Structure 16.2 Data-Driven Testing, Test Verification Activities & Mock Activities 16.3 CI/CD Pipelines with uipcli & Test Manager Traceability
17 Chapter 17: Long-Running Workflows, Action Center & Apps
17.1 Long-Running Workflows: Persistence, Suspend and Resume 17.2 Action Center & Human-in-the-Loop Orchestration 17.3 UiPath Apps: Action Apps, Automations & Integration Service
18 Chapter 18: Trigger-Based Attended Automation & Callouts
18.1 Trigger-Based Attended Automation: Forms, Triggers & Global Variables 18.2 Running Local Triggers & the Event Inspection Tool 18.3 Callouts & Forms for Attended Guidance
19 Chapter 19: UiPath Assistant & Robot Sessions
19.1 UiPath Assistant: Automations, Reminders, Widgets & Configuration 19.2 Robot Session (Picture in Picture): Child Session vs. Virtual Desktop
20 Chapter 20: Autopilot for Developers & Autopilot for Everyone
20.1 Autopilot for Developers: AI Assistance in Studio and Studio Web 20.2 Autopilot for Everyone: Chat, Automations & Clipboard AI
21 Chapter 21: API Automation & Integration Service
21.1 Integration Service: Connectors, Connections & Connector Activities 21.2 API Workflows in Studio Web 21.3 HTTP Requests: Web APIs, the Orchestrator API & Connector Requests 21.4 Connector Builder: Custom Integration Service Connectors 21.5 Integration Service Event Triggers: Connected and Disconnected 21.6 GenAI Activities: Generative AI Inside Workflows
22 Chapter 22: Data Service, Context Grounding & Coded Workflows
22.1 Data Fabric (Data Service) Entities: Modeling Business Data 22.2 Data Fabric Activities and the Platform Connector 22.3 Context Grounding: Retrieval-Augmented Generation with Company Data 22.4 Coded Automations: Structure, Arguments & Invoking Workflows 22.5 Coded Automation Services: Orchestrator, UI Automation, Microsoft 365 & Custom Services
23 Chapter 23: Integrated Scenario Practice
23.1 Integrated Scenario Practice: Designing an End-to-End Solution
22.3 Context Grounding: Retrieval-Augmented Generation with Company Data
Key Takeaways Explain This Topic AI
Context grounding in the AI Trust Layer indexes company documents for retrieval-augmented generation without separate vector databases or model subscriptions.
Indexes use storage buckets or Confluence Cloud, Dropbox, Google Drive, and OneDrive & SharePoint via connections with Files.Read scope.
Supported file types are CSV, DOCX, JPG, JSON, PDF, PNG, TXT, and XLSX, with ten indexes per tenant by default.
Indexes inherit folder permissions, so organize one index per audience and folder path.
Refresh indexes with Update Context Grounding Index, search with Context Grounding Search, and use DeepRAG for PDF analysis.
Last updated: September 2026
22.3 Context Grounding: Retrieval-Augmented Generation with Company Data
Core Concept: Context grounding is part of the AI Trust Layer . It makes business documents usable by UiPath's generative AI features through retrieval-augmented generation (RAG) : documents are indexed as embeddings, the most relevant passages are retrieved for each question, and the model answers using them. No separate embedding model, vector database, or LLM subscription is needed.
Where It Is Used
GenAI Activities , such as Content Generation grounded on an index and Context Grounding Search .
Autopilot for Everyone , to answer questions from company knowledge.
Agents , as a knowledge source.
Indexes and Data Sources
An index holds the embeddings of documents from one data source. Indexes are created and managed in Orchestrator (the folder-level Indexes permission governs them) and are then available across the platform.
- Data source Access
- Orchestrator storage buckets Upload documents directly, through Studio activities, or through the API
Confluence Cloud , Dropbox , Google Drive , Microsoft OneDrive & SharePoint Through Integration Service connections authorized with at least the Files.Read scope
Limits and rules
Supported file types: CSV, DOCX, JPG, JSON, PDF, PNG, TXT, and XLSX.
Index limit: ten indexes per tenant in Automation Cloud, expandable on request.
UiPath recommends a 1:1 relationship between indexes and folder paths in the data source, which keeps data for different audiences separate.
Indexes inherit folder permissions: users without access to the folder cannot view, update, delete, or use its indexes.
Keeping Indexes Current
When documents change, the index must be refreshed:
Use Update Context Grounding Index in a workflow, for example after a process uploads new policy documents.
Schedule regular refreshes for sources that change often.
An Index Completed event lets automations continue when indexing has finished.
- Using Context Grounding in Workflows
- Search, then generate
Context Grounding Search takes a query and returns the most relevant passages from an index.
Pass the passages to Content Generation with instructions such as "Answer only from the provided passages; say you don't know otherwise."
Validate the answer, and log which sources were used.
Grounded content generation
Content Generation can reference an index directly, retrieving context behind the scenes.
DeepRAG
For deeper analysis across documents, a DeepRAG analysis can be run and its result retrieved with Get DeepRAG Analysis by ID . DeepRAG works with PDF documents.
Designing a Good Knowledge Base
Curate the documents. Remove outdated versions, because the index cannot tell which policy is current.
One index per audience and topic, for example "HR policies" and "IT runbooks", matching folder paths.
Prefer text-based documents. Scanned documents with poor quality produce weak passages.
Write clear queries in automations, for example "vacation carry-over rules for employees in Germany" rather than "vacation".
Test with real questions and compare answers to the source documents.
Security and Governance
Folder permissions protect indexes, so place indexes in folders whose members may see the documents.
Data source connections should use accounts that can read only the intended folders.
AI Trust Layer policies govern which AI features may use company data.
Worked Example: HR Question Answering
HR uploads the handbook PDFs and policy documents to a storage bucket in the HR folder.
An administrator creates an index HR-Policies on that bucket.
An attended automation for HR assistants asks for a question, runs Context Grounding Search on HR-Policies, and sends the top passages to Content Generation with instructions to answer only from them and cite the document names.
When HR publishes a new policy, a small process uploads it and runs Update Context Grounding Index .
Employees outside HR cannot use the index, because they lack access to the HR folder.
Exam-Style Scenarios
Scenario 1: Answers quote a policy that was replaced last week. Cause: the index was not refreshed. Fix: run Update Context Grounding Index after publishing new documents, or schedule refreshes.
Scenario 2: A company wants to ground answers in documents stored in SharePoint. Use a Microsoft OneDrive & SharePoint connection with at least the Files.Read scope as the index's data source.
Scenario 3: Legal and HR documents must not be visible to each other's users. Use separate indexes on separate folder paths in separate Orchestrator folders; indexes inherit folder permissions.
Scenario 4: The tenant already has ten indexes and needs another. Consolidate indexes that serve the same audience, or request an increase, because ten per tenant is the default limit.
Common Traps
Forgetting to refresh the index after documents change.
Creating one large index for all departments, which mixes audiences and permissions.
Assuming grounding guarantees correctness; answers still need validation for important decisions.
Using unsupported file types or connections without the Files.Read scope.