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Streamlit Chatbot with Neo4j Aura Integration

Services Covered:

Chatbot Development • AI and Machine Learning
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Industry
Industry

Advertising & Marketing

Duration
Duration

6 months

Budget
Budget

Confidential

Start Date
Start Date

1 May 2025

Team Size
Team Size

1-5

Engagement Model
Engagement Model

Offshore

Project Capability Score (PCS)

gauge meter
81/100
Strong

Project Capability Score (PCS) estimates how capable Steves AI Lab is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

mapVancouver, Canada

Project Summary

Steves AI Lab built a Streamlit-based chatbot that integrates with Neo4j Aura via an MCP middleware to convert natural-language inputs into Cypher queries. The end-to-end solution included the Streamlit frontend, middleware integration and backend connectivity, delivering faster query times, reduced backend complexity, and improved access to graph data for non-technical users. The team delivered on time and communicated via virtual meetings and messaging.

Key Challenges

  • Develop a lightweight, user-friendly Streamlit chatbot
  • Integrate MCP middleware with Neo4j Aura seamlessly
  • Translate natural-language inputs into accurate Cypher queries
  • Present graph data in a clean conversational interface while keeping backend architecture simple and maintainable

Project Deliverables

  • Streamlit chatbot frontend
  • Middleware integration with Neo4j Aura (MCP)
  • Backend logic and database connectivity
  • Natural-language-to-Cypher query translation

Project Solution

Steves AI Lab designed and developed a lightweight AI-driven chatbot using Streamlit that allows users to query Neo4j Aura graph data in natural language. The vendor implemented an MCP middleware layer, backend logic and database connectivity, and focused on simplicity to avoid unnecessary infrastructure complexity while delivering an end-to-end functional solution.

Project Outcome

  • Enabled querying Neo4j Aura in plain English with Cypher translation
  • Achieved faster graph query times (seconds instead of minutes)
  • Reduced backend complexity and dependence on Cypher expertise
  • Delivered the project on time

Platforms

  • WebWeb
  • API/Integration PlatformAPI/Integration Platform

Tech Stack

  • StreamlitStreamlit
  • Neo4jNeo4j

Client Endorsement

Overall Review Rating

4.75star

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Steves AI Lab Pvt Ltd delivered a functional solution that allowed users to query Neo4j Aura using plain English. The team worked quickly, simplified the backend, and made graph data more accessible to non-technical users. Communication was handled through virtual meetings, email, and messaging apps.”

Shay Router

Managing Director

Note: This endorsement is based on publicly available client feedback from external review sources.

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