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AI SYSTEMS TODAY

About

Table of Contents
Our services encompass:
  • Custom AI Development: Designing and implementing AI models to address business challenges.
  • Machine Learning Integration: Embedding machine learning algorithms into existing systems to improve decision-making processes.
  • Data Engineering: Structuring and optimising data pipelines to ensure efficient data flow and accessibility.
  • AI Workshops: Providing training sessions to equip teams with the knowledge and skills necessary to leverage AI technologies effectively.

We utilise various technologies, including cloud-based platforms, to deliver scalable and efficient AI solutions.

At AI Systems Today, we offer a range of chatbot solutions tailored to meet diverse needs, categorised by capabilities and cost considerations:

1. Personal Chatbots
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  • Overview: Ideal for individual use or small-scale applications, these chatbots handle fundamental interactions and automate simple tasks.
  • Technical Stack:
    • Compute: Azure Functions (serverless architecture)
    • Database: Azure Cosmos DB
    • Framework: LangChain.js for Retrieval-Augmented Generation (RAG)
  • Features:
    • Cost-effective with pay-per-use pricing
    • Scalable to accommodate varying workloads
    • Quick deployment with minimal maintenance
  • Use Case Example: A personal assistant chatbot retrieves information from a user’s documents.

2. Standard Chatbots
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  • Overview: Designed for small to medium-sized businesses, these chatbots manage more complex interactions and provide enhanced user experiences.
  • Technical Stack:
    • Compute: Azure App Service
    • Search: Azure Cognitive Search with Semantic Search capabilities
    • AI Integration: Azure OpenAI Service
  • Features:
    • Improved natural language understanding
    • Semantic search for accurate information retrieval
    • Moderate cost with scalable options
  • Use Case Example: A customer support chatbot that understands user queries and provides relevant answers from a knowledge base.

3. Advanced Chatbots for Enterprises
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  • Overview: Suited for large organisations, these chatbots offer sophisticated capabilities, including evaluation, analysis, and fine-tuning, to handle complex interactions and integrate seamlessly with enterprise systems.
  • Technical Stack:
    • Compute: Azure Kubernetes Service (AKS) for containerised deployments.
    • Database: Azure Cosmos DB
    • Search and Analytics:
      • Azure Cognitive Search with Semantic Search
      • Azure Data Explorer (Kusto Query Language - KQL)
    • AI Integration: Azure OpenAI Service
  • Features:
    • Advanced natural language processing with fine-tuning capabilities
    • Integration with enterprise data sources for comprehensive responses
    • Robust analytics and evaluation tools
    • Higher cost, reflecting advanced features and enterprise-grade performance
  • Use Case Example: An internal organisational chatbot that assists employees by providing detailed analytics reports and insights based on company data.

4. Enterprise-Grade Chatbots with Enhanced Data Integration
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  • Overview: Tailored for large-scale enterprises requiring high-performance chatbots with extensive data integration, these solutions combine advanced AI capabilities with robust data management and querying tools.
  • Technical Stack:
    • Compute: Azure Virtual Machines or Azure Kubernetes Service for dedicated resources.
    • Database: Azure Cosmos DB
    • Search and Query:
      • Azure Cognitive Search
      • Azure Data Explorer utilising Kusto Query Language (KQL)
    • AI Integration: Azure OpenAI Service
  • Features:
    • Seamless integration with multiple data sources
    • Real-time data analysis and response generation
    • Customisable AI models tailored to specific enterprise needs
    • Premium pricing commensurate with advanced capabilities and infrastructure requirements
  • Use Case Example: A financial services chatbot that provides clients with real-time investment insights, portfolio analysis, and market predictions by querying vast datasets and performing complex analyses.

By categorising our chatbot offerings in this manner, AI Systems Today ensures that clients can select a solution that aligns with their specific requirements and budget while leveraging the robust capabilities of Azure’s ecosystem.

For detailed pricing information, please refer to Azure’s official pricing pages:

  • Azure AI Bot Service: Azure
  • Azure OpenAI Service: Azure

Details
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These resources provide up-to-date information on the costs associated with each service, helping you make informed decisions based on your specific needs and budget.

Here’s a comprehensive table outlining the categorised chatbot offerings with estimated costs and timelines for development:

Type Category Training Costs Infrastructure Costs/Month Traffic Costs (Tokens) Development Costs (One-Time) Time to Complete
Personal Chatbot Serverless AI Chat with RAG $135 $/GB $50 - $300 (Azure Functions + CosmosDB) $0.005/token (low volume) $3,000–$5,000 2–4 weeks
Standard Chatbot Semantic Search Chatbot $$135 $/GB $300 -$1,500 (Azure App Service + Cognitive Search) $0.01/token (moderate volume) $5,000–$15,000 4–6 weeks
Business Chatbot Enterprise NLP Chatbot $135 $/GB $1,500 -$5,000 (AKS + Cognitive Search + Key Vault) $0.015/token (moderate-high volume) $15,000–$30,000 8–10 weeks
Enterprise Chatbot AI-Powered RAG with KQL $135 $/GB $5,000+ (VMs or AKS + CosmosDB + Azure Data Explorer) $0.02/token (high volume) $30,000–$50,000+ 12–16 weeks

Personal Chatbot
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  • Use Case: Personal assistant or hobby projects.
  • Stack: Azure Functions (serverless), CosmosDB, LangChain.js.
  • Cost Efficiency: Minimal infrastructure costs with basic capabilities.

Standard Chatbot
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  • Use Case: Small businesses or teams needing semantic search capabilities.
  • Stack: Azure App Service, Cognitive Search, Azure OpenAI.
  • Enhanced Features: Semantic search and scalable services.

Business Chatbot
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  • Use Case: Mid-sized businesses requiring custom training and evaluation.
  • Stack: AKS, Key Vault, Azure OpenAI, Cognitive Search.
  • Key Features: Added security and moderate complexity in queries.

Enterprise Chatbot
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  • Use Case: Large-scale enterprise systems with complex data integrations.
  • Stack: Azure Virtual Machines/AKS, CosmosDB, Azure Data Explorer, OpenAI.
  • Advanced Features: Real-time analysis, integration with enterprise data, and high scalability.

Considerations
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  • Training Costs: Depend on the requirement for custom fine-tuning.
  • Traffic Costs: Calculated based on expected token usage in Azure OpenAI pricing.
  • IaaS Costs: Include infrastructure like compute, storage, and networking.
  • Development Costs: Reflect the effort for custom development, integrations, and testing.
  • Time to Complete: Varies based on complexity and customisation needs.