ARiDA by INBISTRA

Set a Research Goal.Get Comprehensive Results.

ARiDA deploys autonomous AI agents that execute complex research workflows—searching literature, analyzing molecules, mapping patents, querying clinical trials—in parallel, without hand-holding.

Autonomous Multi-Agent Workflows
Complex Tasks in 5-20 Minutes
Human Input at Decision Points Only

Research Assistants Answer Questions.ARiDA Executes Research Programs.

Most AI tools need constant prompting. ARiDA takes a research objective, plans an execution strategy, deploys specialized agents, and synthesizes results—autonomously.

Traditional AI Chat

  • One question → one answer → next question
  • You manage the workflow manually
  • Context lost between sessions
  • No persistent state or file management
  • Requires constant attention

ARiDA Autonomous Workflows

  • Define objective → agents plan and execute
  • 18+ specialized agents work in parallel
  • Persistent state across sessions
  • Virtual file system for artifacts
  • Runs autonomously—interrupts only for decisions

How Autonomous Workflows Execute

STEP 01

You Define the Goal

"Map the competitive landscape for GLP-1 agonists in NASH—trials, patents, publications, key players"

STEP 02

ARiDA Plans

Decomposes into tasks, identifies dependencies, selects specialized agents, determines execution order

STEP 03

Agents Execute in Parallel

Literature agent + patent agent + clinical trials agent + web intelligence—all working simultaneously

STEP 04

Synthesized Results

Comprehensive deliverable with findings, citations, visualizations—ask follow-ups or export

18+ Specialized Agents.200+ Scientific Tools.

Each agent is an expert in its domain—with access to the right databases, the right tools, and the right methodology. They collaborate, not compete.

Literature & Evidence

Search millions of papers, extract key findings, synthesize into coherent narratives with proper citations

PubMed/PMC SearchCitation AnalysisSynthesis & Narrative

Molecular Intelligence

Structure analysis, property calculation, bioactivity data, target-disease associations, pathway context

RDKit AnalysisChEMBL QueriesOpenTargets Integration

Clinical & Regulatory

Trial landscape mapping, enrollment status, endpoint analysis, phase-specific regulatory requirements

AACT DatabaseClinicalTrials.gov APIRegulatory Guidance

Patent & IP

Patent landscape mapping, competitor tracking, claim structure analysis, freedom-to-operate assessment

EPO SearchGoogle PatentsClaim Analysis

Scientific Computing

Full Python environment with RDKit, Pandas, NumPy, SciPy, scikit-learn—execute custom analyses on demand

Python SandboxStatistical AnalysisVisualization

Web Intelligence

Real-time web scraping, structured data extraction, company profiles, funding news, pipeline updates

Company ResearchNews MonitoringCompetitive Intel

Built for Life Sciences Workflows

Whether you're mapping literature, analyzing compounds, or navigating regulatory requirements—ARiDA understands the domain.

Research Scientists

Comprehensive evidence synthesis at unprecedented speed

Literature Reviews in Minutes

Launch a review request—return to a synthesized analysis of hundreds of papers with citations, key findings, and identified gaps.

Cross-Database Discovery

One query triggers parallel searches across clinical trials, molecular databases, patents, and grant funding. Connections humans would miss.

Publication-Ready Output

Not bullet points—structured narratives with proper citations, evidence tables, and methodology documentation ready for internal review.

Example Research Workflows

Real tasks that ARiDA executes autonomously—multiple agents working in parallel while you focus elsewhere.

"Map the competitive landscape for GLP-1 agonists in NASH—Phase 2+ trials, key patents, recent publications, and pipeline status of top 10 players"

~15-20 min5 agents in parallel

"Analyze this compound (SMILES) for drug-likeness, calculate ADMET properties, find ChEMBL analogs with bioactivity data, and visualize the structure"

~5-8 minMolecular + Python agents

"Create a literature synthesis on CAR-T manufacturing challenges—key papers from 2022-2024, main bottlenecks, emerging solutions, with proper citations"

~10-15 minLiterature + Synthesis agents

"What are the IND-enabling study requirements for a novel biologic in oncology? EU vs US differences, with ICH/EMA/FDA citations"

~8-12 minRegulatory agent

Every Finding Cited

Full source traceability

Enterprise Security

Your data stays yours

Days → Minutes

Parallel agent execution

Domain-Native

Built for life sciences

Coming Soon

Stop Babysitting Your AI.Start Deploying Research Workflows.

Join life sciences teams using ARiDA to run autonomous research workflows that would take days manually.

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