NeuralChainX
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Domain Agentic AI

For the experts of advanced industry —
from IP-R&D Agent
to AX strategy

Whether you are digging into a hard technical problem or looking for an answer buried in internal documents. The Anneal model and its agents, trained on domain intelligence from semiconductor, display, and AI computing, review and analyse the evidence — automating the most demanding expert work and turning it into intelligence you can act on straight away.

Externally validated Innovation-Growth Venture Company KIBO Technology Guarantee AI Voucher supplier 2026 Outstanding Startup
INDUSTRY & INTERNAL DATA DECISION-READY Patents Papers · research Companies · supply chain Equipment · process logs Internal documents Decision history Agentic AI RAG · LLM Domain Intelligence Data Security R&D IP·Legal Product Operations Sales
01 — The Arc

From solving the hard problem to opening the revenue — one unbroken flow

ACT 01 · Technical challenge
Take on the hardest problem to solve
Researchers · R&D
ACT 02 · Research planning
Turn the answer into a roadmap
R&D planning · IP
ACT 03 · Business opportunity
Turn the roadmap into a sales opportunity
Product planning · BizDev
It gets sharper on the back of past decisions
02 — Engagement model

Shared problems as product; specific governance and workloads as professional services

The judgement work that recurs in every organisation is handled in standardised form by the SaaS products. The company-specific data, policies, and system constraints left on top of that are designed to fit through Professional Services.

03 — The Stack

A four-layer architecture that turns raw big data into decisions

Every result travels the same path. Multiple sources acquire domain meaning in Anneal, the agent team reasons over it, and it comes back as an output you can decide from.

RAW DATA BUSINESS OUTCOME
01
LAYER 01 · SOURCE

Data layer

Patents, papers, public filings, and internal documents are gathered, filtered against reliability criteria, normalised for notation and units, then embedded as semantic vectors.

Patents Papers Signals
02
LAYER 02 · DOMAINCORE

Anneal layer

Domain intelligence and user review history are learned through fine-tuning. It picks up the field's vocabulary, metrics, and trade-offs, and is refreshed by your organisation's decisions.

Embedding Ontology Decision history
03
LAYER 03 · REASONING

Agentic AI layer

Eight specialist agents find evidence, weigh it, and build a plan. A patented data-processing structure keeps AI hallucination in check.

Retrieve Reason Plan
04
LAYER 04 · OUTCOME

Decision-ready output

It comes back in a form each department can use immediately. Review summaries, report drafts, and the next action plan all remain, with their evidence.

Review summary Report draft Action plan
The decisions your team makes travel back up to Anneal and refine the model
04 — Start

Just tell us the one problem that frustrates you most right now

We start with that one case. The evidence and decision from the first review become the starting point of the next cycle.

inquiry@neuralchainx.com