The Platform

Meet Your Network of Specialized AI Micro-Agents.

gaide is not a generalist AI. It is a proprietary System of Intelligence designed to replicate the cognitive processes of Health Technology Assessment (HTA) bodies.

While others focus on summarizing public data, we simulate decisions. We have built a "Hive Mind" of country-specific agents—hard-coded with the intuition of industry experts and trained on decades of payer precedents.

The Architecture

A highly specialized AI system trained on comprehensive set of relevant data

We treat HTA strategy as a high-precision data science problem. Our technology stack moves beyond simple text processing to a rigorous, three-layer pipeline that turns regulatory noise into computable, predictive signals.

01

The Data Refinery

Vertical ETL

02

Granular Feature Engineering

Quantifying Intuition

03

Micro-Agent Network & Integration

Reconstructing Logic

Layer 1

The Data Refinery

Turning Unstructured Noise into a Unified Intelligence Grid.

Raw regulatory data is unstructured and disconnected. A 2024 guideline update might invalidate a 2021 pivotal trial design, but standard search tools won't catch the link.

We have built a Dynamic Intelligence Grid that ingests, cleans, and structures data from disparate sources, creating a unified "single source of truth."

Semantic Evolution Tracking

Our system acts as a "Time Machine," tracking how medical concepts (e.g., "Standard of Care") evolve over decades. We don't just know what the rules are today; we know how they change, allowing us to predict future requirements.

Value Insight: By unifying fragmented regulatory history into a single source of truth, we ensure your strategy is built on the complete picture, not just the visible surface.
Layer 2

Granular Feature Engineering

Quantifying Regulatory Intuition.

The core challenge of HTA is that guidelines are qualitative (text), but prediction requires quantitative data. We bridge this gap by translating regulatory language into math.

Translating Text to Features

We translate qualitative regulatory text into thousands of computable features.

Proprietary Vectorization

Instead of feeding raw text to a model, we engineer proprietary vectors that quantify strategic concepts.

Digitizing Strategy

We turn "regulatory intuition" into math.

Value Insight: This digitization of intuition allows us to stress-test your asset against thousands of historical precedents, revealing risks that human review alone would miss.
Layer 3

The Micro-Agent Network & Integration

Reconstructing the Decision Logic.

We move beyond simple prediction to a complete reconstruction of the assessment process.

Specialized Reconstruction

Each model is country-specific and is task-built to reconstruct exactly how HTA bodies make decisions.

Holistic Synthesis

By merging the outputs of these independent, high-precision models, we construct a comprehensive, multi-dimensional view of the HTA outcome.

Mathematical Logic

We don't just "guess" the result; we mathematically reconstruct the decision logic used by the committee.

Value Insight: The result is a forecast that mirrors the actual committee debate, giving you the foresight to preempt objections and secure your target price.
The Scale of Intelligence

Evidence-Based. Data-Backed. Battle-Tested.

Our models are not hallucinating; they are referencing a massive, structured dataset of historical reality.

20+
Years of Clinical Guidelines
tracked for semantic evolution
15,000+
HTA Decisions
(G-BA, HAS, NICE) ingested and labeled
120,000+
Clinical Trials
analyzed for comparator and endpoint trends
2,500+
Proprietary Features
engineered per therapeutic indication
94%
Prediction Accuracy
verified against historical payer decisions
The "White Box" Standard

Explainability as a Feature.

In the pharmaceutical industry, a "Black Box" prediction is a liability. You cannot base a billion-dollar decision on "The AI said so."

Traceable Logic via RAG (Retrieval-Augmented Generation)

We adhere to a strict "White Box" architecture. Every prediction, risk flag, or recommendation is citations-backed.

We don't just say:

"High risk of rejection."

We say:

"78% Risk of Rejection because the comparator violates G-BA Guideline Section 4 (2023) and mirrors the failure pattern of Asset X (2022)."

This is not just data processing. It is the digitization of strategy.

The New Standard

The Era of Trial and Error is Over.

We have turned the art of Market Access into a solvable science. By replacing subjective guesswork with adversarial simulation, gaide ensures that when you finally face the payer, the outcome is not a gamble—it is a calculated certainty.

Welcome to the new physics of decision-making.

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