Literature review never ends.
Science publishes 5M articles a year. Teams process less than 0.1% of the relevant information. Days of reading and still no clarity on which route is viable for your case.
Arandi·AI FOR R&D DISCOVERY
Clarity before you commit resources.
Water treatmentKnowledge Chat150 PAPERS
What architecture can degrade residual hormones in dairy effluents at room temperature, with a wide operational pH tolerance?Carolina · R&D Director
ARA
Arandi Agent/3 papers cited
A hybrid architecture that no single paper proposes: perovskite as photocatalytic pretreatmentP012 followed by immobilized laccase as enzymatic polishingP037.
Mass balance closes at >97% with OPEX comparable to a conventional MBR. Regulatory risk: the perovskite contains cobaltP089 — evaluate nickel-zinc as an alternative.
3 verified DOIsCROSS-DOMAIN · MATERIALS ↔ BIOTECH
The problem·Hard Tech R&D
If you lead R&D, you already know this loop.
The answer may live in a field you haven’t looked at
In R&D the pattern repeats: the evidence exists in another industry, in another discipline. Arandi finds it and connects it back to your problem.
The cost of being wrong is asymmetric.
In the Fuzzy Front End, early decisions lock in up to 70–80% of a product’s cost. Getting it wrong can mean losses of hundreds of thousands or millions and months on dead-end routes — which is why validating before investing is critical.
What Arandi is
80% of your project’s budget is decided before the first experiment.
Arandi is not a search engine and not a chatbot. It is an intelligence platform that decomposes your technical problem to first principles, searches verified scientific literature, extracts mechanisms document by document, and stays available to query at any time. Every claim traceable to its original source.
How it works·4 steps · 2 decision gates
Four steps. You decide at each one.
Strategic framing
A guided conversation takes your stated problem to its first-principles formulation. The system does not advance until the problem is correctly scoped and you approve it.
Reviewable analysis plan
The system proposes which lines to explore. You approve, modify or remove before a single analysis resource is spent.
Deep corpus analysis
Search across verified literature, mechanism-by-mechanism extraction, classification by role: direct evidence, cross-domain transfer, or context. Between 12 and 25 minutes.
Persistent Knowledge Chat
You converse with your corpus. Every answer cites real papers with traceable badges. When you close, you generate a 2–3 page executive memo ready for the committee.
* Patent coverage on the 2026 roadmap.
What makes us different
We don’t optimize for speed. We optimize for honesty.
Explicit Decision Gates
The system stops twice and waits for your approval before spending resources analyzing the wrong question.
Traceability by design
Every claim points to a verifiable source. If the source does not exist or cannot be validated, the system does not cite it.
Connections across domains
Arandi detects when a solution comes from another field. The difference between finding more of the same and discovering a productive analogy.
Declared degradation
If part of the analysis fails, the output says so up front. No documents that look complete when they aren’t.
Concrete example
Removing micropollutants in the dairy industry.
Client
AquaPure — R&D Director, water treatment
Needs to remove veterinary drugs and residual hormones from industrial effluents. Hard constraints: room temperature, no pH pretreatment, limited OPEX. Three weeks reading papers without convergence.
What happened
Arandi reframed the problem as selective oxidative degradation of polar organic molecules in an aqueous matrix with calcium and lactose interference. It proposed three lines: advanced photocatalysis, immobilized enzymes, regenerable adsorbent materials. Carolina approved all three at Decision Gate 2.
Deliverable
A 3-page executive memo with recommendation, 5 key pieces of evidence, risks, declared gaps and traceable links back to Knowledge Chat.
01Problem
Remove residual hormones and antibiotics from dairy effluents at room temperature, with no pH pretreatment, on a limited OPEX.
02Analysis
Reformulation: selective oxidative degradation of polar molecules in a matrix with Ca²⁺ and lactose. Three routes: photocatalysis · immobilized enzymes · regenerable adsorbents.
03Finding
Hybrid architecture: photocatalytic perovskite + immobilized laccase as polishing. Cobalt regulatory risk documented.
Who it’s for
Arandi is for Chief Scientists and R&D Directors in Hard and Deep Tech
For you if
You decide technical routes with budget on the line.
- You defend those decisions before committees or regulatory audits.
- You lead R&D in an industrial or deep-tech company.
- Your organization values evidence traceability over output speed.
Not for you if
You need a search engine or a summarizer.
- You want a quick summary of a specific paper.
- You expect the system to give you the right answer without your technical input.
- Your problem has a fast answer and does not require deep investigation.
Plans
Start free. Scale with your team.
Free
No card. 90 seconds.
A full Deep Dive on your real problem. No demos, no calls, no mandatory onboarding.
Includes
- 1 active workspace
- Strategic framing + reviewable search plan
- Full Deep Dive · 150 papers analyzed
- Knowledge Chat · 3 turns per workspace
No credit card
Professional
For R&D teams with budget on the line.
Everything in Free, plus team capacity, unlimited conversation and shared memory across projects.
Adds to Free
- 5 simultaneous workspaces
- Unlimited Knowledge Chat
- Cross-workspace library
- Report repository
- Executive memo on demand
- Early access to new features
30 min · Deep Dive on your real case
Your next technical problem·Start today
Do you want to solve it by reading papers for three weeks, or by talking to the evidence in one afternoon?
No card · account in 90 seconds
FAQ
The five questions we hear first.
If you don’t find your question, write to us — we respond fast and in technical language.
Private, isolated workspace with Row-Level Security. We do not train models on your content. Your workspace data never mixes with another organization’s.
It’s the threshold where the marginal cost of analysis is justified by the value of the additional document. More papers does not mean more insight — it means more noise without curation.
Every source goes through DOI verification. If we cannot confirm that the paper exists and that the claim is in the original text, the system does not cite it. No exceptions.
If it’s covered by OpenAlex — engineering, materials, chemistry, biotech, energy, agro, pharma — yes. If not, we tell you before charging you.
On the 2026 roadmap. Closed pilots get priority access when it enters beta.