Temigis
Platform Architecture

Under the Hood:
The Temigis® Architecture

How Temigis delivers consultant-grade life sciences intelligence with the speed and accuracy your business demands.

Intelligent Orchestration Engine

Temigis is built on three layers of purpose-built intelligence.

hub

Orchestrator

Acts as the consultant: interprets each query, identifies the standardised terms within it, and selects the right specialist to answer it.

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Tools

The domain expertise: years of pharmaceutical industry knowledge coded into a step-by-step reasoning process for each type of question.

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Utilities

The data specialists: dedicated components that each understand and assemble their own slice of the data, from IP and litigation to market access and pricing.

At the heart of this is Temigis's proprietary entity-resolution: an automated disambiguation pipeline that resolves every query to the correct drug, company, and geography in your database before any analysis begins.

"If ambiguity exists, Temigis proactively asks for clarification."

Tiered Model Infrastructure

The Orchestrator runs on Amazon Bedrock AgentCore, a managed runtime purpose-built for AI agents, using LangChain's ReAct reasoning pattern with a dual-model architecture for optimal performance:

Claude Haiku 4.5

High-Speed Reasoning & Tool Selection

Claude Opus 4.5

Comprehensive Executive Summaries

A tiered, tenant-isolated memory layer lets Temigis retain relevant facts, preferences, and conversation summaries across sessions, so returning users get continuity without repeating themselves, while every organisation's memory stays private to that organisation.

Data Foundation

A Standardised, AI-Optimised Data Set

Life sciences data is fragmented by nature: regulatory, commercial, and legal information sits in disconnected sources with inconsistent naming and structure. Temigis standardises this data to a proprietary ontology, so every element is consistently retrievable and every drug, company, and geography is resolved to a single, unambiguous entity. This is combined with a Retrieval-Augmented Generation (RAG) pipeline that unifies structured and unstructured data, vectorised with pgvector.

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Unified Knowledge Access

Semantic search is powered by a high-performance Amazon Aurora PostgreSQL instance, allowing Temigis to surface the most relevant information from across your entire knowledge base, combining both SQL queries and vector similarity search. Every piece of content is vectorised using Amazon Titan embeddings, ensuring consistent, high-quality semantic understanding across the entire platform.

Engineered for Performance & Quality

Each specialist capability is built and deployed as its own independent service, engineered for long-term maintainability, faster response times, and the ability to scale as new capabilities are added.

verified Validation Automated Testing
speed Velocity Independently Deployed Services

The system is validated by a rigorous quality framework, with a comprehensive suite of automated tests engineered to deliver consultant-grade accuracy and reliability for every output. The entire system is hosted securely on Amazon Web Services, utilising a serverless architecture with AWS Lambda and API Gateway for seamless scalability.

Some questions require deep, multi-step research across specialist capabilities, and Temigis is built to handle that gracefully. Long-running queries are processed asynchronously with built-in safeguards, so complex analysis is never rushed, cut short, or lost mid-way through.

Explainable, not black-box. Every response comes with a transparent paper trail: named sources and traceable logic that show exactly how Temigis arrived at its answer. In life sciences, conclusions need to stand up to scrutiny, not just sound plausible.

Enterprise-grade security is built in from the ground up: web application firewall protection, role-based access control, and strict tenant isolation ensure your organisation's data stays private and secure.

Built on Amazon Web Services

Temigis runs entirely on AWS, giving life sciences organisations the reliability, security, and data governance they expect from enterprise infrastructure. AI processing is routed through Australia and the broader Asia-Pacific region, keeping inference close to home and grounded in local regulatory and legal logic, not a generic global default.

database

Managed, Scalable Data Layer

A serverless Amazon Aurora PostgreSQL database automatically scales with demand, with connection pooling for consistent performance under load, alongside Amazon DynamoDB for fast, reliable session handling.

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Enterprise Identity & Access

Amazon Cognito secures every account with optional multi-factor authentication and adaptive, risk-based protection, backed by role-based access for administrators, power users, and standard users.

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Data Protection

All data is encrypted at rest, database infrastructure has no direct path to the public internet, and administrative actions are captured in a dedicated, long-retention audit trail.

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Resilient by Design

Infrastructure spans multiple Availability Zones for resilience, with continuous monitoring and alerting across the platform to catch issues before they affect users.

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Temigis is built for the people who make high-stakes life sciences decisions: commercial, regulatory, IP, and strategy teams who need consultant-grade analysis at the speed their business demands.

It's not a replacement for expert judgement. It's what elevates your best people out of manual research and into high-impact strategy.

Built by experts. Guided by context.

Designed to help life sciences leaders think faster and act smarter.