Merge pull request #403 from neo4j-documentation/update-aura-agent-page

Updating Aura Agent Product Page To Latest

Author: zach-blumenfeld

modules/genai-ecosystem/images/aura-agent-diagram.png

@@ -10,7 +10,7 @@
 **** https://neo4j.com/labs/genai-ecosystem/google-cloud-demo[GraphRAG with Google Vertex AI^]
 
 *** Neo4j GenAI Product Integrations
-**** xref:aura-agent.adoc[Aura GraphRAG Agents]
+**** xref:aura-agent.adoc[Neo4j Aura Agent]
 **** xref:graphrag-python.adoc[GraphRAG Python Package]
 **** https://python.langchain.com/docs/integrations/providers/neo4j[LangChain Neo4j (Vendor Supported Package)^]
 **** xref:vector-search.adoc[Vector Index and Search]

modules/genai-ecosystem/nav.adoc

@@ -515,7 +515,7 @@ You've successfully built and deployed a knowledge graph agent using Neo4j Aura
 
 == Resources
 
-* See the http://neo4j.com/docs/aura/aura-agent/[documentation^] for a more in-depth details on Neo4j Aura Agent
+* See the https://neo4j.com/docs/aura/aura-agent/[documentation^] for a more in-depth details on Neo4j Aura Agent
 * Additional worked examples are continually added to the https://github.com/neo4j-product-examples/knowledge-graph-agent[GitHub Repository^]
 * The https://neo4j.com/product/aura-agent/[Neo4j Aura Agent webpage^] and https://neo4j.com/developer/genai-ecosystem/aura-agent/[developer guide^] contains a general overview with links to additional videos and learning resources
 

modules/genai-ecosystem/pages/aura-agent-getting-started.adoc

@@ -1,4 +1,4 @@
-= Aura GraphRAG Agents
+= Neo4j Aura Agent
 include::_graphacademy_llm.adoc[]
 :slug: aura-agent
 :author: 
@@ -8,22 +8,31 @@ include::_graphacademy_llm.adoc[]
 :page-pagination:
 :page-product: aura
 
-Aura Agent, in early access from Oct 2025, is an agent-creation platform that enables users to rapidly build, test, and deploy AI agents grounded by their own enterprise data in AuraDB. 
+image::https://dist.neo4j.com/wp-content/uploads/20250929164049/aura-agent-tools-e1759250930497.png[]
+
+Neo4j Aura Agent, is an agent-creation platform that enables users to rapidly build, test, and deploy AI agents grounded by their own enterprise data in https://neo4j.com/product/auradb/[AuraDB].
 It provides end-to-end automated orchestration and AIOps for graph-based knowledge retrieval. 
 The platform abstracts away the complexity of integrating diverse LLM and agentic frameworks, GraphRAG retrieval patterns, text-to-query generation (via specialized Text2Cypher models), and secure agent-serving infrastructure. 
 
-image::https://dist.neo4j.com/wp-content/uploads/20250929164049/aura-agent-tools-e1759250930497.png[]
+== Key Capabilities
+
+image::aura-agent-diagram.png[Aura Agent Diagram, width=600]
+
+The key capabilities of Neo4j Aura Agent include:
+
+* *Graph-Driven Agent Creation*: Auto-generate a ready-to-deploy draft agent in minutes with tailored prompts and tools customized to your graph schema and use case(s).
+* *Accurate Agentic GraphRAG*: Improve relevance with robust graph retrieval tools: vector search, query templates & text-to-query.
+* *Rapid Testing & Iteration*: Test, refine, and evaluate agent behavior in a built-in low-code playground UI. Easily add, remove, and edit tools.
+* *Advanced Reasoning & Explainability*: Enhance trust with transparent chain-of-thought and multi-hop graph reasoning exposed through Neo4j Aura Agent's reasoning tab and response format
+* *Single-Click Deployment (MCP & REST)*: Simplify your AI stack with secure, hosted, MCP & REST endpoints in the cloud
 
-Among the key capabilities of Aura Agent:
+Watch the 5-minute demo for details!
 
-* Agent creation in the Aura console with a no-/low-code agent builder
-* Agent retrieval tools for pre-defined graph query templates, vector similarity search, and text to query
-* Agent testing via a playground chat UI 
-* Secure agent deployment for consumption by downstream apps via an authenticated endpoint, with MCP support coming soon
+video::rdtP73IT6tc[youtube, width=800, height=450]
 
 == Prerequisites
 
-You can use Aura Agent with the following Aura offerings
+You can use neo4j Aura Agent with the following Aura offerings
 
 * AuraDB Free
 * AuraDB Pro (incl. Pro Trial)
@@ -34,123 +43,26 @@ The database must not be paused to use it in an agent.
 You need to have *"Generative AI assistance" enabled* in your Aura Organization, then Aura Agents should be visible in the sidebar.
 
 == Getting Started
+See the xref:aura-agent-getting-started.adoc[getting started tutorial] and https://neo4j.com/docs/aura/aura-agent/[documentation]
+to understand how to begin using Neo4j Aura Agent.
 
-Navigate to the Agents entry in the sidebar, select "Create Agent" and provide
-
-* Title
-* Description
-* Instructions
-
-And most critically your Aura database to run on (requirements see above).
-
-You can test your agent continually in the chat on the right hand side.
-
-Then start adding *specific tools* to your agent to give it the capabilities to retrieve certain subsets of data or convert user questions into Cypher queries.
-Currently the agent only supports _read only_ queries against the database.
-
-Don't forget to save your agent, when you're satisfied with the current state.
-
-image::https://dist.neo4j.com/wp-content/uploads/20250930120034/test-agent-aura-console.png[]
-
-You can choose to share your agent internally with other project members, or make it available *externally* through an API (currentl REST, soon MCP and A2A).
-
-== Available Tools
-
-=== Cypher Template Tool
-
-The *Cypher Template Tool*, executes a parameterized, read-only Cypher statement against the database and returns the results directly to the agent.
-
-You need to provide a _name_ and _description_ of the tool for the agent to use and _cypher_ query and an optional set of parameters.
-
-Some notes:
-
-* make sure to return only relevant information from the query
-* best return only select node and relationship attributes (text, numbers)
-* don't return embeddings or graph elements like node / relationship / paths 
-* try to de-duplicate the results
-* limit the results to 10 to 50 rows so that the agent/LLM is not overwhelmed with too much irrelevant information
-* test the Cypher statements of your tools beforehand to ensure that they work correctly
-
-image::https://dist.neo4j.com/wp-content/uploads/20250930112819/get-contract-details-tool.png[]
-
-=== Text2Cypher Tool
-
-The "Text2Cypher" allows the agent to retrieve data dynamically that is either not covered by other tools or more structural in nature (like aggregations).
-
-The infrastructure will pass the _text from the tool invocation_, together with the retrieved database _schema_ and the _text2cypher system prompt_ to a fine-tuned model to generate a suitable Cypher statement to execute.
-
-For this tool you only need to provide a _description_ and _instructions_.
-
-The instructions should cover:
-
-* When to use the Text2Cypher tool (and when not)
-* Specific aspects about your database, domain
-* Relevant entities and especially information about searchable categorical properties, e.g. shape of identifiers
-* Which attributes are suitable for aggregation
-
-=== Vector Similarity Tool
-
-The *Vector Similarity Tool* allows to find nodes in your graph by vector similarity.
-
-Besides a description you provide
-
-* Embedding Model Provider (Vertex AI, OpenAI)
-* Embedding Model
-* Vector Index Name
-* Top-K results
-
-And the tool will then embed the input text from the agent, perform the vector search and return the top-k results to the agent for processing.
-
-== API Usage
-
-To integrate the Aura Agent into your system, you can make it available externally, so it is callable via a REST API.
-
-Besides the `ENDPOINT_URL` you also need `CLIENT_ID` and `CLIENT_SECRET` as https://neo4j.com/docs/aura/aura-cli/initial-configuration/[API keys from your User Profile^], to create short lived session tokens.
-
-The example code below uses https://jqlang.org/[`jq`] for command line JSON processing.
-
-[source,shell]
-----
-export CLIENT_ID="..."
-export CLIENT_SECRET="..."
-export ENDPOINT_URL="https://api.neo4j.io/v2beta1/projects/.../agents/.../invoke"
-
-# assign bearer token to environment variable
-export BEARER_TOKEN=$(curl -s --request POST 'https://api.neo4j.io/oauth/token' \
-     --user "$CLIENT_ID:$CLIENT_SECRET" \
-     --header 'Content-Type: application/x-www-form-urlencoded' \
-     --data-urlencode 'grant_type=client_credentials' | \
-     jq -r .access_token)
-
-#invoke endpoint
-curl --request POST \
-  "$ENDPOINT_URL" \
-  -H 'Content-Type: application/json' \
-  -H 'Accept: application/json' \
-  -H "Authorization: Bearer $BEARER_TOKEN" \
-  -d '{"input": "<YOUR AGENT QUESTION>"}' \
-  --max-time 60 | jq .
-----
-
-////
-# get bearer token
-curl --request POST 'https://api.neo4j.io/oauth/token' \
-     --user "$CLIENT_ID:$CLIENT_SECRET" \
-     --header 'Content-Type: application/x-www-form-urlencoded' \
-     --data-urlencode 'grant_type=client_credentials'
-
-{"access_token":"eyJh....","expires_in":3600,"token_type":"Bearer"}
-////
+== Use Case Examples
+See the https://github.com/neo4j-product-examples/knowledge-graph-agent/[Worked Examples Repository^] for applying Aura Agent to various use cases including:
 
-The example repository contains example code for https://github.com/neo4j-product-examples/knowledge-graph-agent/tree/main/code/contract-review-mcp[wrapping the REST API into an MCP server].
+* Legal Contract Review,
+* Know Your Customer (KYC)
+* Human Resources & People Analytics
 
 == Resources
 
+* https://neo4j.com/docs/aura/aura-agent/[Documentation^]
+* https://neo4j.com/blog/agentic-ai/neo4j-launches-aura-agent/[Blog^]
 * https://neo4j-aura.canny.io/changelog/aura-agent-preview[Aura Agent Feedback^]
-* https://github.com/neo4j-product-examples/knowledge-graph-agent/blob/main/contract-review.md[Example Agents Repository^] - Contract Review, Know Your Customer (KYC)
-* https://neo4j.com/blog/genai/build-context-aware-graphrag-agent/[Neo4j Aura Agent: Create Your Own GraphRAG Agent in Minutes^]
-* https://docs.google.com/document/d/1c2w3JM7IoDMOjBY50twMtNgY2Q3VrNtM7dQQPGolxw0/edit?tab=t.0#heading=h.ygp8gdk80zp5[Aura Agent FAQ^]
 * https://graphacademy.neo4j.com/courses/workshop-genai/[GraphAcademy Workshop^]
+* xref:aura-agent-getting-started.adoc[Getting Started Tutorial]
+* https://github.com/neo4j-product-examples/knowledge-graph-agent/[Worked Examples Repository^]
+//* https://neo4j.com/blog/genai/build-context-aware-graphrag-agent/[Neo4j Aura Agent: Create Your Own GraphRAG Agent in Minutes^]
+//* https://docs.google.com/document/d/1c2w3JM7IoDMOjBY50twMtNgY2Q3VrNtM7dQQPGolxw0/edit?tab=t.0#heading=h.ygp8gdk80zp5[Aura Agent FAQ^]
 
 // * https://www.youtube.com/watch?v=edYZ8AZXsKQ[Aura Agent Livestream^]
 ////