Research
Collect pathway evidence
/// Biological Simulation >>>
Simulating agentic humans? Everyone does it.
/// autonomous agents >>>
Cells, proteins, genes — each modeled as an autonomous LLM agent with its own profile, memory, and adaptive behavior.
Network
Core nodes
Ring 1
Signal hubs
Ring 2
Leaf agents
Ring 3
Each agent carries its biological identity — chemical makeup, receptor density, and signaling history — reflecting on past interactions to determine its next action.
Agents execute deterministic biological processes, but adapt through special-case responses when new conditions like drugs or mutations are introduced.
Three tiers of biological relationships govern how agents discover and influence each other across the network.
/// simulation pipeline >>>
Five visual phases, live-streamed status, side-by-side outcomes.
Collect pathway evidence
Map entities + edges
Configure twin scenarios
Run adaptive agents
Surface clinical deltas
/// capabilities >>>
Cells, proteins, genes as active agents
Instant baseline vs intervention split
Web citations directly into graph
Phase events as they happen
RL and metaheuristics for search
Multi-source biology context
/// intelligence pipeline >>>
We research your pathway and compound, assemble a validated network of agents and phases, then run paired simulations and distill everything into a single comparative narrative.
Five-stage pipeline
Discover
Pathway & compound research
Forge
Network & agent factory
Blueprint
Phased simulation plan
Execute
Dual-scenario simulation
Synthesize
Comparative intelligence
01
Discover
02
Forge
03
Blueprint
04
Execute
05
Synthesize
Platform stack
4 layersPathway Intelligence
Research-grade pathway & drug context
Agent & Network Forge
Validated graph, targets, timed phases
Phased Simulation Core
Batched runs · baseline vs. intervention
Live Pipeline Stream
Phase-by-phase visibility as it runs
Synthesize report
Comparative intelligence
Pipeline signals
Research depth
Phase coverage
Scenario lift
Stream health
/// knowledge sources >>>
Key biological databases spanning gene, protein, pathway, disease, and molecular resources routinely leveraged during simulation—ensuring our agents reflect grounded biology.
Internal search engine and expanded database planned for v1.0
/// get started >>>
Be the first to explore LLM-powered agent-based biological simulation. Define your pathway, introduce a drug, and watch autonomous agents interact.
Korvus
/// get in touch
Have questions, feedback, or just want to chat?
Reach atrithvik_sabnekar@berkeley.edu or book a demo