Adaptive Hypothesis Collider (AHC)The AI System That Thinks Like a Researcher
Why AHC Matters
Many AI tools automate tasks or assist workflows, but AHC does something far deeper: it reasons, hypothesizes, and self-audits.
It accelerates the front-end of discovery — transforming open-ended research challenges into novel, testable pathways.
Each result comes with full transparency, governance, and reproducibility, giving you ideas you can trust, verify, and build on.
What AHC Is
Cognitive Research Architecture
AHC is a full-stack architecture designed to think, not just respond. It weaves together mechanisms for domain understanding, cross-domain synthesis, self-evaluation, and audit logging.
Novelty Generator with Prior-Art Awareness
By integrating a Prior-Art Radar and Sidecar search, AHC ensures ideas are not just imaginative — they are strategically novel relative to existing knowledge.
Reasoning Engine with Governance
Every hypothesis passes through internal logic checks, falsifiability filters, and governance rules — ensuring ideas are credible before they reach you.
Reproducibility & Audit Trail System
AHC’s Run Ledger captures every decision, transformation, and score — with cryptographic integrity — so you can reconstruct and verify each insight end-to-end.
How AHC Works — At a Glance
State Your Research Challenge
You bring your open question, hypothesis gap, or R&D problem.
Map the Domain + Identify Tensions
AHC models your field’s landscape—highlighting constraints, conflicting goals, and unsolved tensions.
Harvest Cross-Domain Analogies
The system searches for structural patterns in distant disciplines and maps them into your domain context.
Generate & Score Hypotheses
AHC proposes multiple candidates, rigorously assessing originality, practicality, and testability.
Refine & Package with Traceability
The top ideas are polished, tied to validation paths, and delivered with a full, auditable reasoning trail.
The final product is more than an idea. It’s an audit-ready Research Dossier you can act on, validate, or publish.
Key Benefits for You
Speed: compress the front end of research — go from question to hypothesis in days, not months
Transparency: trace exactly how each idea was formed, evaluated, and vetted
Credibility: outputs come with provenance, test plans, and governance consistency
Originality: ideas often cross domains in ways humans rarely do
Reproducibility: every run’s reasoning and results can be revisited, audited, and re-executed with the same setup
Use Cases & Deployment
AHC is purpose-built for high-uncertainty research domains where insight must lead innovation.
Ideal applications include:
Novel materials discovery, where new composites or alloys are needed
Drug mechanism ideation, unlocking paths beyond traditional screening
Sustainable process design, fusing ecology and engineering logic
Strategic foresight and science roadmapping, charting future R&D directions
What clients receive:
A complete research package:
Research Dossier — deep, novel hypotheses grounded in domain logic
Operationalisation Annex — actionable test plans ready for experiments
Ledger Proof — an auditable record of reasoning and validation
This package is designed not just to inspire ideas, but to deliver trust, repeatability, and strategic clarity.
Begin Your AHC Run
Every great discovery starts with a question.
AHC transforms that question into a structured, reproducible pathway toward new knowledge.
Start your first run and see how machine reasoning, governed by scientific integrity, can accelerate your research beyond the conventional curve.
Frequently Asked Questions
What makes AHC different from other AI systems?
AHC isn’t a chatbot, “agent” or automation tool — it’s a governed cognitive architecture designed to generate novel, testable, and reproducible research hypotheses. Each run produces a complete, auditable dossier suitable for academic or industrial R&D use.
How does AHC ensure reproducibility?
Every AHC run is recorded in a Run Ledger, documenting reasoning steps, evaluation scores, and governance checks. The same setup can be re-executed to verify process fidelity — meeting the reproducibility standards of academic research.
Can universities or research teams use AHC in publications?
Yes. AHC’s structure and documentation are designed for integration into formal research workflows. Several university pilots have already validated AHC outputs for academic use.
Is AHC safe for proprietary or confidential projects?
Absolutely. All runs are executed under strict confidentiality and data isolation. No client data or results are shared or reused outside your engagement.
What do I receive after an AHC run?
Each client receives a Research Dossier, Operationalisation Annex, and Ledger Proof — providing complete transparency from hypothesis generation to validation roadmap.
How long does a typical run take?
Most runs are completed within 7–10 working days, depending on scope and complexity.
What areas of research can AHC be applied to?
AHC is domain-agnostic. It has been used in materials science, biomedical research, sustainability, and strategic foresight — anywhere new ideas and structured reasoning are needed.
How much does it cost to run AHC?
Pricing varies by complexity and number of runs. Entry-level academic pilots start from NZ$15,000, with full commercial R&D programmes available on request.
Can AHC be customised for our organisation?
Yes. The system can be configured to align with specific research priorities, governance rules, or data environments.
Who operates the AHC runs?
All runs are executed and governed by The Thought Factory AI Lab, founded by Nik Nigro, the architect of the AHC system.