The AI kit for Research and Development Engineers

Runs the full literature review: search, summarize, synthesize, cluster, gap-check and cite, so you get a sourced review instead of scattered PDFs.

Compares material properties, compatibility, cost and compliance, for example ranking three polymers for a housing that must survive 120 C.

Optimizes a design across parameters, cost, weight and reliability, for example trimming bracket mass 15 percent without losing stiffness.

Builds sourced reports on markets, competitors, trends and regulations, for example mapping who else is filing patents in your sensor niche.

Like "Build An Academic Database Search Strategy"

Like "Assess Material Compatibility in Specific Conditions"

Like "Analyze Market Trends"

Like "Data Scraping and Structuring"

A validated, reproducible working dataset with raw data untouched.

An analysis working copy in which every calculation uses consistent, documented units.

A fair, source-linked methods comparison.

An evidence-based explanation for a replication discrepancy, or a documented open question.

Build this to stop re-finding old papers and test reports, keeping provenance and review state attached to every file.

Build this to ask questions across specs and standards and get answers traced back to the exact clause.

Build this to cut search, extraction and citation work while keeping every claim in your report traceable.

Build this to watch only the papers that match your narrow relevance rules, with inspectable inclusion decisions.

Build a throwaway terminal or UI prototype to answer one design question fast.

Runs automated test suites and reports coverage results for your project.

Analyzes code repositories, documentation, and technical implementations for informed decisions.

Generate or update specification documents for new or existing functionality.