What is neuro-symbolic AI?

Neuro-Symbolic AI combines neural networks (for understanding language) with symbolic reasoning systems (for applying rules with mathematical certainty). Reshuffle.AI's Reasonex applies a deterministic, symbolic reasoning layer over the domain's governed rules — so reasoning is mathematically necessary, not statistically probable.

Reasonex is Reshuffle.AI's neuro-symbolic reasoning engine for regulated industries. The LLM never reasons; the reasoning engine never guesses. Every inference is auditable and reproducible.

Which industries does Reshuffle.AI serve?

Legal intelligence, clinical decision support, financial regulatory compliance, insurance underwriting and claims, telecom SLA and regulatory compliance, and ontology quality assurance.

What is the research basis for Reasonex?

Reasonex's symbolic reasoning capabilities are developed with the team behind Algebraic Machine Reasoning (Xu, Vaidya, Wu, Chandra, Lai & Chong, CVPR 2023), which achieved 93.2% on the I-RAVEN benchmark, exceeding the human baseline of 84.4%.

Where is Reshuffle.AI based?

Reshuffle.AI is based in Singapore and has been selected into SUTD's ARISE venture-building programme, run by SUTD's Venture, Innovation & Entrepreneurship (VIE).

MikeROS™Now officially available on Claude for Legal

Only hallucination-free Legal AI that reasons like a lawyer

Name: Reasonex
Brand: Reshuffle.AI

Most lawyers settle for the best citation they can find — not the best one they should have. MikeROS changes that. It’s the only Legal AI that reasons like a lawyer: reasoning from the nature of your case to surface the authority you need, then building the reasoning chain step by step, with zero hallucination in the reasoning and every link locked to verified law.

Hallucination-Free

The reasoning, citations, and conclusions are derived by a symbolic engine, not generated by an LLM — so on covered law they cannot be invented. Where a question falls outside scope, MikeROS says so rather than guessing.

Structural Search for Citations

MikeROS finds authority by the underlying structure of your case, not just its surface wording — surfacing the on-point precedent that ordinary search overlooks.

Reasoning Chains

It builds the argument the way a lawyer does — step by step, each link locked to a verified rule and a real authority, with a complete trace you can follow and defend.

A team of litigation associates and paralegals

Legal AI that invents citations is a malpractice risk

The hard part of legal AI isn’t writing fluent prose — it’s being right. Tools built on large language models are designed to predict the most likely next words, not to find the correct answer, so they will confidently cite cases that were never decided, misstate the holdings of the ones that were, and wrap it all in reasoning that reads as authoritative but cannot be checked. A 2025 Stanford and Yale study in the Journal of Empirical Legal Studies found hallucinated or erroneous output in 17–33% of answers from the leading commercial legal-AI tools. In litigation, a single fabricated citation can sink a filing — or a career. “Usually right” is not a standard the profession can work to.

You can’t fully trust the legal advice you get from your current AI.

Your team burns billable hours double-checking AI research it can’t verify.

On-point precedents get missed, because the AI can’t reason the way a lawyer does.

These aren’t workflow problems. They’re a fundamental limit of how general-purpose legal AI is built.

The difference is provability

MikeROS keeps the fluency of an LLM for understanding the question, but moves every decision onto a deterministic reasoning engine that can show its work.

Generic legal AI

LLM predicts the answer
Citations may not exist
No proof of correctness
Hope it's right

MikeROS

LLM understands the question
Reasonex reasons deterministically
Every citation verified against live databases
Provably correct, with a full audit chain

Read. Reason. Prove.

Three layers, each doing only what it is good at — so the reasoning is necessary, not probable.

Read

Neural language understanding turns a plain-English legal question into structured legal intent. The LLM listens — it never decides the answer.

Reason

The Reasonex engine applies jurisdiction-specific rules through symbolic, deterministic inference — constructing a formal logical proof rather than a probable guess.

Prove

Every output ships with a complete audit chain: the answer, the citation, the paragraph, the applicable rule, and the full reasoning behind it.

MikeROS architecture: a plain-English legal query passes through a neural perception layer, into a symbolic reasoning layer that maps factual patterns, legal conditions and outcomes, and out as a deterministic response with a zero-hallucination, auditable reasoning chain — Plain-English query in, deterministic legal opinion out — the reasoning happens in the symbolic layer, never the language model.

Where litigators put it to work

Contract review

Clause-by-clause analysis with the reasoning shown for every flag.

Precedent research

Structural fact-pattern matching that finds on-point cases, not keyword neighbours.

Procedural computation

Deadlines and rules-of-court calculations derived directly from the governing rules.

Document drafting

Court document drafting with forms compliance built in.

Compliance verification

Regulatory checks traced end-to-end against the applicable framework.

Training & QA

Associate training and quality review with transparent, reviewable reasoning.

Why it holds up in practice

Verified citations only

Every citation is checked against live legal databases. If a source can’t be verified, it isn’t cited.

Jurisdiction-native rules

The rules engine reasons over the actual rules of court for each jurisdiction — not a generic approximation.

Full audit trail

Every answer carries its logical proof chain, so the reasoning can be checked, defended, and relied upon.

Data stays in-jurisdiction

Data residency is enforced by the architecture, not bolted on as a policy.

Deploy it the way that fits your firm

Standalone app

A web-based interface your team can use directly — no integration required.

REST API

Programmatic integration with your practice-management and document systems.

Claude for Legal

Officially available on Claude for Legal — call MikeROS from inside your Claude workflow as a specialist legal tool.

MCP server

Deploy MikeROS as an MCP server for any other MCP-compatible assistant or agent platform.

Whichever the model, your data stays within your jurisdiction by design.

Now available

MikeROS is officially available on Claude for Legal

Lawyers working in Claude can now call MikeROS directly for deterministic procedural reasoning over Singapore’s Rules of Court — every citation locked to a verified authority, every step of the reasoning traceable — without leaving their workflow. MikeROS connects as a specialist tool through the open Model Context Protocol (MCP), bringing provable, court-ready reasoning to the platform where lawyers increasingly already work.

Inside your Claude workflow

Connects over MCP, so a lawyer can call MikeROS as a specialist tool without leaving Claude.

Every citation verified

Each authority is locked to a real, verified source — nothing is invented or approximated.

Deterministic, not generated

The legal reasoning is derived by the symbolic engine, so it can be checked and defended.

FAQ

See MikeROS on your jurisdiction

Live demonstration · Proof-of-concept · Firm pilot