Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Conspecta is an innovative, web-based research platform that integrates various functionalities including microscopy image analysis, flow cytometry, molecular biology, sample tracking, and the creation of publication-ready figures into a single cohesive workspace. This platform effectively eliminates the need for the disparate tools that many laboratories typically piece together, ensuring that data, samples, and results remain interconnected throughout the entire process from experimentation to final figure generation, all while providing comprehensive traceability. It is particularly tailored for biology labs that emphasize imaging and flow cytometry, as well as for new principal investigators and early-stage biotechnology companies. Unlike platforms that cater to regulated or clinical environments, Conspecta remains research-focused and accessible, offering free access for individual users while providing paid plans for teams that include shared workspaces to foster collaboration. With its user-friendly interface and robust features, Conspecta empowers researchers to streamline their workflows and enhance productivity.
Description
At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system.
The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.
API Access
Has API
Yes
API Access
Has API
No
Integrations
ChatGPT
Yes
Claude
Yes
Claude Desktop
Yes
Claude Science
Yes
Cursor
Yes
Gemini for Science
Yes
Microsoft Copilot Studio
Yes
Microsoft Excel
Yes
SnapGene
Yes
Integrations
ChatGPT
No
Claude
No
Claude Desktop
No
Claude Science
No
Cursor
No
Gemini for Science
No
Microsoft Copilot Studio
No
Microsoft Excel
No
SnapGene
No
Pricing Details
$0
Free for you and one collaborator, every workspace included. Paid plans open it to the whole lab and add additional storage, AI object detection, external integrations via API, and bring-your-own AI assistant integration.
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Conspecta
Founded
2025
Country
United States
Website
conspecta.bio
Vendor Details
Company Name
Iris.ai
Founded
2015
Country
Norway
Website
iris.ai/
Product Features
Product Features
Data Extraction
Disparate Data Collection
No
Document Extraction
No
Email Address Extraction
No
IP Address Extraction
No
Image Extraction
No
Phone Number Extraction
No
Pricing Extraction
No
Web Data Extraction
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Qualitative Data Analysis
Annotations
No
Collaboration
No
Data Visualization
No
Media Analytics
No
Mixed Methods Research
No
Multi-Language
No
Qualitative Comparative Analysis
No
Quantitative Content Analysis
No
Sentiment Analysis
No
Statistical Analysis
No
Text Analytics
No
User Research Analysis
No