Public Roadmap
Here's what we've shipped, what we're building, and what's coming next. Don't see your compound class? Request it below.
Shipped
50 Compound Classes
Comprehensive coverage including arylpropionic acids, morphinans, beta-blockers, NSAIDs, and more—each with independent accuracy metrics and confidence intervals.
Expanded Therapeutic + Agrochemical Coverage
50 compound classes spanning pharmaceuticals and agrochemicals — including NSAIDs, CCBs, opioids, antipsychotics, antifungals, amino-alcohols, kinase atropisomers, pyrethroids, and triazole fungicides — gated into Tier 1, Tier 2, and Tier 3 with independent accuracy metrics and Wilson CI confidence intervals.
Kinase Atropisomer Expansion
Dedicated support for atropisomeric kinase inhibitors with specialized validation protocols.
Wrong Predictions Browser
Searchable interface for all wrong predictions with per-compound-class error breakdown, accuracy bars, sorting, and filtering. Full transparency on every incorrect call.
3D Molecule Viewer
Interactive 3D visualization of predicted stereochemistry on shareable prediction pages. Real molecular structures from PubChem with auto-rotation.
Dashboard + API v1
Full-featured user dashboard for managing predictions, storage modes, and data. RESTful API v1 for programmatic access with API key authentication.
In Progress
Founding Customer Program
10 exclusive annual seats at $9,995/year with rate locks, first access to new compound classes, and roadmap input.
Academic Tier
Free tier for .edu users with 100 predictions/month and API access for non-commercial research.
Batch Prediction Mode
Process hundreds or thousands of compounds in a single submission with structured CSV/SMILES input.
Planned
Python Package
Install and use ChiralCall directly in Python: pip install chiralcall. Full API bindings and batch processing support.
Additional Compound Classes
Taxanes, statins, antiretrovirals, and community-requested scaffolds. Fluoroquinolones and oxazolidinones have already shipped.
R Package
Seamless integration for R users: install.packages("chiralcall") with full tidyverse compatibility.
Don't see your compound class?
Request a new scaffold and we'll prioritize validation if it has ≥10 known compounds.