Watch private R&D knowledge become a ranked experiment plan.
The customer’s documents stay inside the customer’s own environment. ACRAZO runs in a private cloud, on-prem server, or offline workstation. The demo below shows the workflow: public materials context + customer-controlled private documents + AI-ready memory + ranked next experiments.
ACRAZO output
From scattered files to decision-ready science.
The demo is intentionally visual. It shows the buyer what the private pilot feels like without promising a magic black-box formula generator.
Select environment
Private cloud, on-prem server, or offline workstation.
Upload privately
Customer loads documents into their own ACRAZO environment.
Build memory
Vector retrieval connects formulas, tests, complaints, and technical notes.
Reason with context
ACRAZO compares public knowledge with company-specific history.
Rank next tests
The system proposes a short experiment list for expert approval.
“Improve corrosion resistance without increasing VOC.”
The user enters a target property, constraints, available raw materials, and customer failure history. The private LLM retrieves relevant internal evidence and generates a ranked plan.
What the buyer should understand.
- ACRAZO does not need the client to email secret files to ACRAZO.
- The private pilot can run where the client chooses to keep data.
- The demo shows a guided workflow: not generic chat, not a full LIMS replacement.
- Recommendations are ranked for expert review, DOE planning, and customer-ready communication.
- The goal is to reduce wasted trials and help the team reach the first useful experiment set faster.
From 250,000 possible paths to five experiments before the coffee gets cold.
This section is designed to make the buyer feel the power of the private Science LLM: broad search, private memory, fast filtering, then a short expert-reviewable plan.
A private R&D sprint while the chemist takes one sip.
The user enters a target such as: improve corrosion resistance, keep VOC stable, avoid yellowing, preserve adhesion and use only approved raw materials.
- Public materials context frames the chemistry.
- Private documents provide company-specific evidence.
- The LLM narrows the design space into ranked next tests.
Five experiments worth running first.
Test two inhibitor ratios against historical corrosion failures.
Check adhesion loss risk before increasing anti-corrosion loading.
Recreate customer field conditions in a short validation matrix.
Compare early hardness, water resistance and final film integrity.
Generate a technical response without exposing the confidential formula.
The page should feel like the product is thinking.
For the buyer, the demo shows motion: upload, index, retrieve, reason, rank and draft. For the engineering team, it remains realistic: the first pilot can be a guided workflow using private retrieval, templates, guardrails and controlled outputs.
1. Upload privately
TDS, MSDS, Excel tests, old formulas, complaints and service notes stay in the client-controlled environment.
2. Build R&D memory
The system connects ingredients, constraints, historical failures, customer segments, test methods and expert notes.
3. Produce useful outputs
Ranked experiment plans, DOE drafts, failure diagnosis notes and customer-ready technical answers.
ACRAZO does not claim to replace your chemists. It helps them avoid the wrong 249,995 directions.
The pilot is strongest when the buyer sees an expert-reviewable result: why these five tests, what internal evidence supported the ranking, what risk remains, and what can safely be sent to the customer.
- Evidence map: which documents were used.
- Confidence labels: high, medium, weak or missing-data.
- Experiment logic: target, variables, constraints and expected signal.
- Customer language: technical but confidential-formula safe.
Customer-ready technical response draft
Based on the available internal test history, the most likely route is not a full binder change. The first validation should compare surface preparation sensitivity, inhibitor ratio and cure window before altering the main resin package. We recommend five controlled trials and a short customer explanation focused on application conditions, film build and validation timing.
The buyer sees a private AI lab assistant, not a static brochure.
Before the buyer downloads the guide, the page demonstrates the commercial promise: private evidence goes in, the system narrows the search space, and the chemist receives a short, reviewable path instead of another spreadsheet maze.
From noise to action.
ACRAZO visualizes the journey from public materials context and company-private memory to a ranked set of five practical experiments.
Input target
Improve corrosion resistance, avoid yellowing, keep VOC stable, preserve adhesion, and use only approved raw materials.
Private evidence
Old test results, technical service notes, TDS/MSDS files, customer complaints, field conditions and approved raw materials stay in the client environment.
AI output
Five next experiments, ranked risks, missing data, internal evidence map and a customer-safe answer draft.
Download the ACRAZO private R&D Science LLM pilot guide.
The PDF explains the pilot logic, client-controlled deployment, AI-ready R&D memory, private formulation workflows, security questions, experiment-ranking logic, and what an R&D director should evaluate before buying a private Science LLM.
Download Science LLM Buyer Guide