Pitagora Capital & Consulting LLC proudly holds the status of an AWS Registered Partner, demonstrating our commitment to leveraging advanced cloud technologies to optimize financial decision-making for our clients.

Enterprise cloud for GenAI & ML on AWS — availability, performance, security & FinOps by design.

We built around six pillars—operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability—

A detailed diagram illustrating a machine learning data pipeline, including components like Athena, Amazon S3, DynamoDB, Amazon Bedrock, Lambda, API Gateway, Aurora PostgreSQL, Amazon EC2, s3 storage, and various processes such as data ingestion, embedding, query generation, and response delivery.

Customise Agent - Powered by AWS Bedrock

    • Cloud-based knowledge engines for research, compliance, and auditing with full traceability.

    • Governance & augmented analytics that transform raw data into secure insights and actionable recommendations.

    • Process automation agents to streamline internal workflows and extend value to institutional clients.

    • Fine-tuned models (Amazon Nova, Titan, Claude, Cohere, Llama) adapted privately with your datasets for domain-specific accuracy.

    • Custom model import to securely integrate your own models inside AWS Bedrock.

    • Enterprise connectors (Aurora, OpenSearch, MongoDB, Salesforce, Confluence, SharePoint) for data-driven decisions at scale.

    • Secure orchestration via AWS Lambda, ensuring multi-step tasks and API calls are executed under strict IAM policies.

    • Session memory & auditability to keep context across interactions and guarantee compliance reporting.

    • Advanced analytics agents capable of data visualization, optimization, and risk analysis, supporting regulated industries like finance, supply chain, and manufacturing.

    • Prompt management & governance: design reusable, compliant prompts across workflows while enforcing security and access control policies.

Flow diagram of an AWS cloud architecture showing users accessing a web UI, connected to AWS Amplify, Amazon API Gateway, and Amazon Cognito. These interact with AWS Lambda functions, which connect to Amazon Bedrock, Knowledge Bases, Amazon S3 for documents, Amazon OpenSearch, and Large Language Models like Claude 3, Mistral, Llama, for processing and storage.

Knowledge Bases - Secure RAG for Enterpise

    • Fully managed RAG workflow: from ingestion to retrieval, without custom integrations.

    • Multi-source knowledge: combine repositories, databases, and APIs to enrich models with up-to-date intelligence.

    • Secure data connectors: integrate seamlessly with Amazon Aurora, OpenSearch, MongoDB, Pinecone, Redis Enterprise Cloud, plus enterprise apps (Salesforce, Confluence, SharePoint – in preview).

    • Compliance-first architecture: enforce governance and security across sensitive datasets while ensuring auditability and access control.

    • Retrieve API: fetch context-aware, relevant results directly from enterprise knowledge bases.Scalable knowledge engines: support industries that demand high accuracy and traceability—finance, supply chain, and regulated environments.

Diagram illustrating a data processing workflow with data sources, Amazon Kinesis Data Streams, Amazon Redshift, Amazon Managed Grafana, Amazon Simple Notification Service, and an operations team receiving alerts.

Advanced Analytics - Intelligent Insights with Memory & Optimization

    • Memory-aware agents: retain past interactions for personalized, context-rich insights.

    • Complex data analysis: interpret and process structured and unstructured data at scale.

    • Data visualization & optimization: transform raw datasets into actionable dashboards and optimized strategies.

    • Equation solving & automation: handle advanced calculations, scenario modelling, and workflow optimization.

    • Prompt management: create, save, and reuse prompts securely across multiple workflows.

    • Dynamic parameterization: adjust inference settings and variables to adapt prompts to different enterprise use cases.

    • Secure architecture: enforce IAM and compliance controls, ensuring analytics are traceable and reliable in regulated industries like finance, supply chain, and auditing.

We provides intelligent infrastructure for financial markets, powered by AI and Autonomous Cloud Architectures.

  • End-to-End GenAI Architectures

    Design and deploy retrieval-augmented generation (RAG) pipelines, customised agents, and knowledge bases on Amazon Bedrock, enabling secure and domain-specific AI adoption.

  • Machine Learning & Advanced Analytics

    Full lifecycle from data preparation to model training, fine-tuning, and deployment, building predictive models for forecasting, risk analysis, and optimisation.

  • Consulting & Advisory in AWS

    Strategic consulting for compliance, governance, and security frameworks, with tailored solutions for finance, supply chain, and regulated industries.

  • Data Engineering & Data Lakes

    Build secure and scalable data pipelines, ETL/ELT workflows, and data lakes on AWS (S3, Glue, Redshift, Lake Formation) to unlock real-time and historical analytics.

  • A flowchart diagram illustrating a machine learning workflow with sections for Data Source, Machine Learning, Generative AI, User Authentication, and Data Visualization. It includes icons for S3 Buckets, Databases, APIs, AWS Lambda functions, Amazon DynamoDB, AWS Glue, Amazon Bedrock, Lambda, Amazon Bedrock REST API, LLM Model, Chat Interface, and QuickSight Data Visualization.

    High-Frequency Algorithmic Trading

    Architect and implement low-latency trading platforms using QuickFIX and AWS services, ensuring secure connectivity, millisecond-level execution, and risk controls for institutional trading.

  • A digital diagram illustrating an AWS architecture with public and private subnets, security groups, load balancer, ECS service, ECS cluster, task definition, roles, and repositories.

    Microservices & Cloud-Native Architectures

    Design and orchestrate containerised applications with EKS, ECS, and Lambda, leveraging service meshes, event-driven patterns, and CI/CD pipelines for scalable, fault-tolerant systems.

  • Flowchart illustrating a process in AWS cloud for document processing, including steps such as user authentication, content extraction, review, and retrieval using various AWS services like DynamoDB, SQS, Lambda, S3, Bedrock, and Amazon Textract.

    Customised Enterprise Solutions

    Hybrid and multi-cloud strategies integrating databases, APIs, and enterprise applications, enabling automation, observability, and business agility.