technical overview
how a run becomes an artifact
from question to a planned run, a grounded result, and the artifact and record behind it. anthropic direct, or anything openrouter reaches — your own key, or your own hardware.
the pipeline
five steps between a question and a result.
- query
natural language query
describe what you need in plain english — a target, a compound, or a research question.
- intent
intent detection
the runtime interprets the request and routes it toward the capabilities that can answer it.
- model
provider selection
the language layer uses the configured model path, with the model choice kept separate from the biomedical work.
- tools
tool execution
the selected tools execute through the runtime and pass their outputs into the next required step.
- quality
quality evaluation
results are checked, grounded, and returned as interactive cards with their source context.
- intent detection
- 12 domain templates with confidence thresholds — routes queries to the right tool cluster without explicit user selection.
- provider cascade
- the configured model path is selected before execution; provider details stay behind the runtime contract.
- execution pipeline
- the runtime resolves tools, applies the required controls, executes the work, and preserves the returned outputs.
- quality guard
- quality checks distinguish grounded output from incomplete or degraded generation before it is presented as a result.
500+ scientific tools
each tool is typed, normalized and rendered.
- structure prediction
protein folding (esmfold, openfold), binding site detection, homology modeling, and structure alignment.
- molecular generation
de novo design (genmol), fragment growing, scaffold decoration, and safe fragment ingestion.
- property prediction
admet profiling, toxicity screening, drug-likeness filters, solubility prediction, and medchem alerts.
- synthesis planning
retrosynthetic routes, reaction feasibility, vendor sourcing (zinc, molport), and cost estimation.
- literature & databases
pubchem, uniprot, chembl, wikidata, clinical trials, patent search, and citation extraction.
- target assessment
druggability scoring, binding pocket analysis, selectivity prediction, and cancer genomics (tmb/msi).
- genomics & multi-omics
bulk/single-cell rna-seq, deseq2, variant calling, epigenomics, and hi-c 3d genome analysis.
- molecular docking
diffdock, gnina, colabdock, mm-gbsa rescoring, and pose visualization with mol*.
canvas & passports
every result renders as a card you can work with.
- typed result cards
the result registry maps tool outputs to an appropriate interactive view, with a generic fallback when no bespoke view exists.
- domain sub-renderers
domain-specific renderers handle structures, docking poses, plots, and other scientific result shapes.
results from multiple tools are aggregated into a single compound passport — a unified view of everything known about a molecule. a passport is what a chain of tools produces together; it is an output of the platform, not the thing the platform is.
- admet →
- docking →
- synthesis →
- vendors →
- literature →
- compound passport
one ledger, every surface
every client writes to one auditable ledger.
the runtime under .bloom* is pleach — a fair-source agent runtime whose typed audit row gives you per-run provenance, deterministic replay, and time-travel checkpoints.
the platform runs on vercel (next.js) with serverless gpu compute on modal.com and postgresql on supabase. the cli connects to the same backend for headless and batch workflows.
- modal.com
- hosted GPU compute for the scientific workloads that need it, with provenance attached to the resulting run.
- supabase
- the persistence layer stores session and provenance data used to reconnect results to the work that produced them.
- cli
- ivybloom reaches the same runtime for terminal, batch, and headless workflows.
- next.js 14
- react 18
- typescript 5.9
- tailwind css 4
- zustand
- react query
- vercel ai sdk
- rdkit
- mol*
- 3dmol
- cytoscape
ready to try it?