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Pauling

Full company profile

uuid004lzqw

Namestring
Pauling
Legal namestring
Pauling.AI
Websiteurl
pauling.ai
Company typeenum
Private
Founded yearint
2024
Descriptiontext

Pauling.AI is a Boston-based, venture-backed company founded in 2024 that has developed Autochem, a conversational AI-driven autonomous drug discovery platform. The platform orchestrates 15+ computational chemistry pipelines including GPU-accelerated molecular docking (Uni-Dock, derived from AutoDock Vina), all-atom molecular dynamics simulations (GROMACS with AMBER99SB-ILDN force field), MM-PBSA binding free energy analysis, P2Rank binding pocket prediction, MolProbity and PoseBusters quality control, and ADMET property prediction across 80+ endpoints. The system integrates state-of-the-art third-party AI models (Boltz, DiffDock, AlphaFold 2/3) with physics-based methods via multi-LLM AI agents, running on Google Cloud Dataflow with auto-scaling infrastructure. Target users are medicinal chemists and research scientists who can describe a protein target in plain language and receive validated drug candidates without computational chemistry expertise.

The company serves biopharmaceutical companies, academic research labs, longevity-focused biotechs, and medicinal chemistry personnel, with pain points centered on 10–15 year drug discovery timelines, $2.6B per-approval costs, and 90% industry failure rates. Revenue is generated primarily through a $10,000 standard hit screening package covering 10 million compound docking plus MD validation for the top 100 candidates with approximately one-week turnaround, supplemented by custom enterprise pricing for pharmaceutical leaders and tailored multi-year contracts for academic and ongoing research collaborations. The go-to-market combines enterprise field sales (demo requests via [email protected]) with a product-led growth motion through the self-serve web interface at autochem.pauling.ai, supported by content marketing (Substack blog, The Pauling Principle podcast) and earned media coverage in tech and longevity publications.

Short descriptiontext

Pauling.AI is a Boston-based company offering Autochem, an autonomous AI drug discovery platform that orchestrates molecular docking, dynamics, and ADMET prediction through a conversational interface for biopharma, academic, and longevity biotech customers lacking computational chemistry expertise.

Operating statusenum
Operating
Ownership categoryenum
Headcount rangeband
1–10
akta.pro rankint
HeadquartersBoston, United States
HQ citystring
Boston
HQ countrystring
United States
HQ regionstring
North America
Markets served

Serves global market

Offices1 record

Each record includes

City, Country, Type, Description, Source

Keyword5 values
autonomous drug discovery, AI drug discovery, computational chemistry platform, virtual screening software, molecular dynamics simulation
Industry2 codes
1AI/ML Platforms for Drug Discovery & Experiment Optimization
CodeHLAGAJAOPrimaryYes
2AI/ML-Enabled Biologic Discovery Platforms (computational design, in silico screening)
CodeHLAAAIAEPrimaryNo
NAICS code2 codes
  • Research and Development in Biotechnology (except Nanobiotechnology)541714
  • Scientific Research and Development Services5417
SIC code1 code
  • Services-Prepackaged Software7372
Product category
AI Drug Discovery Platform
Social media profiles2 records
GTM motion2 records

Each record includes

Type, Description, Source

Revenue model2 records
1Project-Based Drug Discovery Services
TypeOne Time License
Description

Standard hit screening package priced at $10,000 covering 10M compound docking plus MD validation for top 100 candidates. Turnaround time is approximately 1 week. Custom pricing available for ongoing research collaborations, academic institutions, and multi-target projects.

pauling.ai
2Enterprise Platform Access
TypeSubscription Recurring
Description

Enterprise customers can access the platform for autonomous drug discovery. Pricing likely varies based on scope and usage, with tailored solutions for pharmaceutical leaders.

pauling.ai
Marketing channels5 records

Each record includes

Title, Type, Stage, Description, Source

Distribution channels2 records

Each record includes

Title, Type, Scope, Target buyer, Description, Source

Cost components5 values
Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales
Pricing details2 tiers
1Standard Hit Screening Package
ModelUnit PricingBilling cadencePay-as-you-go
Notes

$10,000 per project. Includes 10 million molecule docking, MD validation for top 100 candidates, ADMET profiling, and full ranked hit list with binding poses and simulation data. Turnaround approximately 1 week.

pauling.ai
2Academic/Ongoing Collaboration
ModelHybridBilling cadenceMulti-year contract
Notes

Custom pricing for academic institutions and ongoing research collaborations. Multi-target projects receive tailored pricing. Contact [email protected] for quote.

pauling.ai
GTM typeB2B
B2B
Offering typeSoftware
Software
Brand1 record
1Autochem
Description

The computational drug discovery platform developed by Pauling.AI that automates molecular docking, molecular dynamics, and ADMET property prediction through AI agents.

pauling.ai
Core offering1 text field

Pauling.AI operates the Autochem platform, a fully autonomous drug discovery system that lets users describe a protein target (e.g., '6VC8') in plain language and then automatically orchestrates molecular docking, molecular dynamics (GROMACS), ADMET prediction, and quality control to deliver validated drug candidates in days. The platform sells both standardized hit screening services (e.g., 10M-compound docking + MD validation for $10,000) and enterprise-grade platform access tailored to pharmaceutical, biotech, academic, and longevity research customers.

Differentiator
Functional benefit
Problem solved
Quantifiable outcome1 of 5 values shown
  • 85% timeline reduction from initial hit identification to validated lead series
+4 more records
Product overview1 text field

Pauling.AI is a fully autonomous computational drug discovery platform that combines AI agents, enterprise-scale cloud infrastructure, and the latest AI models (Boltz, DiffDock) with physics-based computational chemistry methods. The core product is Autochem, which enables researchers to describe their target in plain language and receive validated drug candidates in days rather than years. Key offerings include: Hit Screening (docking up to 10 million compounds with MD validation); Docking Protocol (GPU-accelerated virtual screening with automated structure preparation and pocket prediction); Counterscreening Protocol (selectivity-focused dual-site docking); and MD/MM-PBSA ΔG Protocol (all-atom molecular dynamics with rigorous binding free energy calculations). The platform integrates with major compound libraries (Enamine, mCule) and protein structure databases (PDB, AlphaFold, UniProt) to deliver end-to-end automation of computational chemistry workflows.

Product and service6 records
1Autochem
CategoryAutonomous drug discovery SaaS platform
Description

The primary fully autonomous computational drug discovery platform that enables researchers to go from protein target to validated drug candidates in days through a conversational AI interface. It orchestrates molecular docking, molecular dynamics, ADMET prediction, and binding affinity analysis without requiring computational chemistry expertise, and is sold to pharmaceutical, biotech, and academic customers.

2Hit Screening
CategoryVirtual screening service
Description

Large-scale virtual screening service that docks up to 10 million compounds and applies MD validation for the top candidates. Delivers high-confidence hits with ADMET profiling and MM-PBSA free energy analysis in approximately 1 week for $10,000, targeting pharmaceutical and biotech researchers.

3Docking Protocol
CategoryComputational chemistry workflow
Description

Virtual screening by molecular docking protocol using GPU-accelerated Uni-Dock. Includes automated structure acquisition, receptor preparation, P2Rank pocket prediction, two-stage docking, and PoseBusters quality control, designed for medicinal chemists conducting early-stage hit identification.

4Counterscreening Protocol
CategoryComputational chemistry workflow
Description

Selectivity-focused virtual screening workflow that docks compounds against two binding sites simultaneously and ranks candidates by a selectivity score to identify selective binders over anti-targets. Used by medicinal chemists who need to profile off-target activity.

5MD / MM-PBSA ΔG Protocol
CategoryComputational chemistry workflow
Description

Molecular dynamics hit validation protocol using all-atom MD simulations in explicit solvent followed by MM-PBSA binding free energy analysis. Includes GROMACS-based MD, AMBER99SB-ILDN force field, TIP3P water model, and per-residue energy decomposition for hit confirmation.

6Enterprise
CategoryEnterprise software tier
Description

Enterprise tier offering for pharmaceutical companies featuring AI-native molecular discovery, physics-grounded explainable predictions, and scalable cloud infrastructure for accelerating R&D pipelines, with custom pricing and tailored solutions.

Scale indicator9 records

Each record includes

Type, Value, Description, Source

Partnership3 partners
Strategic tierCoreTypeTechnology or Integration
Description

Enamine is a major supplier of in-stock screening compounds. Pauling.AI's default screening libraries include approximately 10 million in-stock compounds from Enamine, prioritized because in-stock compounds eliminate procurement delays and allow immediate experimental validation.

Strategic tierCoreTypeTechnology or Integration
Description

Compound supplier providing in-stock screening libraries. Part of Pauling.AI's ~10 million in-stock compound library for virtual screening.

Strategic tierCoreTypeTechnology or Integration
Description

Cloud infrastructure provider powering Pauling.AI's platform. Runs on Google Cloud Dataflow with enterprise-grade security and IP protection for processing millions of compounds in parallel.

Recent move6 records

Each record includes

Date, Type, Title, Description, Source

Expansion highlight5 records

Each record includes

Type, Description

Peers10 records
TypeDirect peer
Description

AI and quantum physics-based drug discovery platform combining computation with automated robotic wet-lab synthesis. Closely comparable to Pauling.AI's in-silico-to-validation pipeline, with a stronger wet-lab component and broader pharma partnerships.

TypeDirect peer
Description

AI drug discovery platform using atom-level convolutional neural networks for structure-based small molecule design. Closely comparable technology stack and customer base (pharma/biotech hit discovery), directly serving the same virtual screening use case Pauling.AI targets.

TypeDirect peer
Description

AI-native drug discovery company using physics-informed machine learning for structure-based design and small molecule discovery. Comparable technology approach (combining physics-based and AI methods) and shared customer base in pharma/biotech.

TypeDirect peer
Description

AI-driven precision medicine and drug discovery company using active learning and patient-derived data for molecule design. Comparable end-to-end AI drug discovery competitor with established pharma partnerships and an existing platform around automated compound design.

TypeDirect peer
Description

Public computational chemistry platform offering physics-based molecular simulation and drug design software. Directly comparable as the established 'complex tools' competitor named explicitly on Pauling.AI's comparison page, serving the same pharma/biotech customers with overlapping workflow tooling.

TypeDirect peer
Description

AI drug discovery company applying machine learning to biomedical knowledge graphs and target identification. Comparable as another end-to-end AI pharma company pursuing the same thesis of compressing the early drug discovery funnel through automation.

TypeBroad incumbent
Description

Alphabet/DeepMind-backed drug discovery company leveraging AlphaFold and related foundation models. Comparable as a well-capitalized AI drug discovery competitor that Pauling.AI's stack explicitly integrates (AlphaFold, Boltz/DiffDock are included as workflow components).

TypeDirect peer
Description

AI-driven drug discovery company combining generative chemistry, target discovery, and clinical development. Comparable as one of the most well-funded end-to-end AI drug discovery competitors pursuing the same 'compressed timelines' thesis with much larger capital and longer operating history.

TypeEmerging player
Description

Emerging AI-native drug discovery platforms building workflow automation around generative biology and chemistry models — comparable as a similarly-staged early entrant in the same 'AI workflow for scientists' category as Pauling.AI.

TypeDirect peer
Description

AI-native drug discovery company combining high-throughput biology with machine learning across a broader phenotypic and target-based discovery footprint. Comparable as a competing AI drug discovery platform with significantly more capital and pipeline depth.

Market position
Strengths4 records

Each record includes

Headline, Details, Source

Weaknesses4 records

Each record includes

Headline, Details, Source

Competitive moat3 records

Each record includes

Type, Details

Key risks6 records

Each record includes

Headline, Details, Source

Key highlights6 records

Each record includes

Headline, Details, Source

Customer concentration

Classification, Details

Named customers1 record

Each record includes

Name, Industry, Type, Use case, Source, UUID

Segment4 records

Each record includes

Title, Type, Primary, Description, Pain point addressed, Use case, Source

Ideal customer profile3 records

Each record includes

Profile, Firmographic size, Sales motion, Sales cycle length, Buying structure, Purchase trigger, Buyer persona, Geography, Industry vertical, Primary use case, Description, Pain points, Evidence proof points, Target buyer

Technology focused
Yes
API detail
Has APIbool
No

Docs URL, Description

Integration35 records

Each record includes

Title, Type, Description, Source

AI capability8 records

Each record includes

Type, Description, Source

AI maturity
App detail

Has app

Feature8 records

Each record includes

Title, Differentiator, Description, Source

Core technology
Revenue estimate
Valuation estimate
Number of profiles
No data
No data
Funding overview

Funding stage, Last funding date, Total funding USD

Funding rounds1 record

Each record includes

Round, Amount USD, Date, Pre money valuation, Total investors, Investors, News

Investors1 record

Each record includes

Name, Type, Date of entry, Rounds participated, Website

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Each record includes

Name, Acquisition type, Announced date, Completed date, Status, Website, News

Investment

Each record includes

Name, Round, Announced date, Lead investor, Website, News

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Pauling

AI Drug Discovery Platformpauling.ai

Pauling.AI is a Boston-based company offering Autochem, an autonomous AI drug discovery platform that orchestrates molecular docking, dynamics, and ADMET prediction through a conversational interface for biopharma, academic, and longevity biotech customers lacking computational chemistry expertise.

What Pauling does

Pauling.AI is a Boston-based, venture-backed company founded in 2024 that has developed Autochem, a conversational AI-driven autonomous drug discovery platform. The platform orchestrates 15+ computational chemistry pipelines including GPU-accelerated molecular docking (Uni-Dock, derived from AutoDock Vina), all-atom molecular dynamics simulations (GROMACS with AMBER99SB-ILDN force field), MM-PBSA binding free energy analysis, P2Rank binding pocket prediction, MolProbity and PoseBusters quality control, and ADMET property prediction across 80+ endpoints. The system integrates state-of-the-art third-party AI models (Boltz, DiffDock, AlphaFold 2/3) with physics-based methods via multi-LLM AI agents, running on Google Cloud Dataflow with auto-scaling infrastructure. Target users are medicinal chemists and research scientists who can describe a protein target in plain language and receive validated drug candidates without computational chemistry expertise.

The company serves biopharmaceutical companies, academic research labs, longevity-focused biotechs, and medicinal chemistry personnel, with pain points centered on 10–15 year drug discovery timelines, $2.6B per-approval costs, and 90% industry failure rates. Revenue is generated primarily through a $10,000 standard hit screening package covering 10 million compound docking plus MD validation for the top 100 candidates with approximately one-week turnaround, supplemented by custom enterprise pricing for pharmaceutical leaders and tailored multi-year contracts for academic and ongoing research collaborations. The go-to-market combines enterprise field sales (demo requests via [email protected]) with a product-led growth motion through the self-serve web interface at autochem.pauling.ai, supported by content marketing (Substack blog, The Pauling Principle podcast) and earned media coverage in tech and longevity publications.

Pauling firmographics

Firmographics
Name
Pauling
Legal name
Pauling.AI
Website
https://pauling.ai
Company type
Private
Founded year
2024
Operating status
Operating
Headcount range
1–10 employees
Short description
Pauling.AI is a Boston-based company offering Autochem, an autonomous AI drug discovery platform that orchestrates molecular docking, dynamics, and ADMET prediction through a conversational interface for biopharma, academic, and longevity biotech customers lacking computational chemistry expertise.
Ownership category
akta.pro rank

Pauling industry classification

Industry
Product category
AI Drug Discovery Platform
NAICS
Research and Development in Biotechnology (except Nanobiotechnology) (541714), Scientific Research and Development Services (5417)
SIC
Services-Prepackaged Software (7372)
akta.pro primary industry
AI/ML Platforms for Drug Discovery & Experiment Optimization (HLAGAJAO)
akta.pro secondary industry
AI/ML-Enabled Biologic Discovery Platforms (computational design, in silico screening) (HLAAAIAE)

Keywords

  • Autonomous drug discovery
  • AI drug discovery
  • Computational chemistry platform
  • Virtual screening software
  • Molecular dynamics simulation

Where Pauling is headquartered

Location

Headquarters

HQ city
Boston
HQ country
United States
HQ region
North America

Offices1 record

Markets served

Pauling business model

Business model
GTM type
B2B
Offering type
Software
Cost components
Technology or R&D, Personnel, Infrastructure, Operations, Marketing or Sales

Revenue model

  1. Project-Based Drug Discovery Services: Standard hit screening package priced at $10,000 covering 10M compound docking plus MD validation for top 100 candidates. Turnaround time is approximately 1 week. Custom pricing available for ongoing research collaborations, academic institutions, and multi-target projects.
  2. Enterprise Platform Access: Enterprise customers can access the platform for autonomous drug discovery. Pricing likely varies based on scope and usage, with tailored solutions for pharmaceutical leaders.

Pricing tiers

ModelBillingPrice
Unit PricingPay-as-you-goStandard Hit Screening Package
HybridMulti-year contractAcademic/Ongoing Collaboration

Go-to-market motion2 records

Distribution channels2 records

Marketing channels5 records

Pauling product offering

Product offering

Core offering

Pauling.AI operates the Autochem platform, a fully autonomous drug discovery system that lets users describe a protein target (e.g., '6VC8') in plain language and then automatically orchestrates molecular docking, molecular dynamics (GROMACS), ADMET prediction, and quality control to deliver validated drug candidates in days. The platform sells both standardized hit screening services (e.g., 10M-compound docking + MD validation for $10,000) and enterprise-grade platform access tailored to pharmaceutical, biotech, academic, and longevity research customers.

Product overview

Pauling.AI is a fully autonomous computational drug discovery platform that combines AI agents, enterprise-scale cloud infrastructure, and the latest AI models (Boltz, DiffDock) with physics-based computational chemistry methods. The core product is Autochem, which enables researchers to describe their target in plain language and receive validated drug candidates in days rather than years. Key offerings include: Hit Screening (docking up to 10 million compounds with MD validation); Docking Protocol (GPU-accelerated virtual screening with automated structure preparation and pocket prediction); Counterscreening Protocol (selectivity-focused dual-site docking); and MD/MM-PBSA ΔG Protocol (all-atom molecular dynamics with rigorous binding free energy calculations). The platform integrates with major compound libraries (Enamine, mCule) and protein structure databases (PDB, AlphaFold, UniProt) to deliver end-to-end automation of computational chemistry workflows.

Differentiator

Problem solved

Functional benefit

Brands

  • Autochem: The computational drug discovery platform developed by Pauling.AI that automates molecular docking, molecular dynamics, and ADMET property prediction through AI agents.

Products and services

  • Autochem The primary fully autonomous computational drug discovery platform that enables researchers to go from protein target to validated drug candidates in days through a conversational AI interface. It orchestrates molecular docking, molecular dynamics, ADMET prediction, and binding affinity analysis without requiring computational chemistry expertise, and is sold to pharmaceutical, biotech, and academic customers.
  • Hit Screening Large-scale virtual screening service that docks up to 10 million compounds and applies MD validation for the top candidates. Delivers high-confidence hits with ADMET profiling and MM-PBSA free energy analysis in approximately 1 week for $10,000, targeting pharmaceutical and biotech researchers.
  • Docking Protocol Virtual screening by molecular docking protocol using GPU-accelerated Uni-Dock. Includes automated structure acquisition, receptor preparation, P2Rank pocket prediction, two-stage docking, and PoseBusters quality control, designed for medicinal chemists conducting early-stage hit identification.
  • Counterscreening Protocol Selectivity-focused virtual screening workflow that docks compounds against two binding sites simultaneously and ranks candidates by a selectivity score to identify selective binders over anti-targets. Used by medicinal chemists who need to profile off-target activity.
  • MD / MM-PBSA ΔG Protocol Molecular dynamics hit validation protocol using all-atom MD simulations in explicit solvent followed by MM-PBSA binding free energy analysis. Includes GROMACS-based MD, AMBER99SB-ILDN force field, TIP3P water model, and per-residue energy decomposition for hit confirmation.
  • Enterprise Enterprise tier offering for pharmaceutical companies featuring AI-native molecular discovery, physics-grounded explainable predictions, and scalable cloud infrastructure for accelerating R&D pipelines, with custom pricing and tailored solutions.

Quantifiable outcome

  • 85% timeline reduction from initial hit identification to validated lead series
  • +4 more outcomes

Companies that use Pauling

Customer profile

Named customers1 record

Segments4 records

Ideal customer profiles3 records

Pauling technology and API

Technology

Technology focussed Yes

API detail

Has API
No
API docs
API detail

Core technology

AI maturity

App detail

Integration35 records

AI capability8 records

Feature8 records

Pauling partnerships and signals

Strategic signal

Partnerships

Three partnerships are on record, tiered core.

  • EnaminecoreTechnology or IntegrationEnamine is a major supplier of in-stock screening compounds. Pauling.AI's default screening libraries include approximately 10 million in-stock compounds from Enamine, prioritized because in-stock compounds eliminate procurement delays and allow immediate experimental validation.
  • mCulecoreTechnology or IntegrationCompound supplier providing in-stock screening libraries. Part of Pauling.AI's ~10 million in-stock compound library for virtual screening.
  • Google CloudcoreTechnology or IntegrationCloud infrastructure provider powering Pauling.AI's platform. Runs on Google Cloud Dataflow with enterprise-grade security and IP protection for processing millions of compounds in parallel.

Scale indicators9 records

Recent moves6 records

Expansion highlights5 records

Pauling competitors and assessment

Company assessment

Direct peers

  • XtalPi: AI and quantum physics-based drug discovery platform combining computation with automated robotic wet-lab synthesis. Closely comparable to Pauling.AI's in-silico-to-validation pipeline, with a stronger wet-lab component and broader pharma partnerships.
  • Atomwise: AI drug discovery platform using atom-level convolutional neural networks for structure-based small molecule design. Closely comparable technology stack and customer base (pharma/biotech hit discovery), directly serving the same virtual screening use case Pauling.AI targets.
  • Iambic Therapeutics: AI-native drug discovery company using physics-informed machine learning for structure-based design and small molecule discovery. Comparable technology approach (combining physics-based and AI methods) and shared customer base in pharma/biotech.
  • Exscientia: AI-driven precision medicine and drug discovery company using active learning and patient-derived data for molecule design. Comparable end-to-end AI drug discovery competitor with established pharma partnerships and an existing platform around automated compound design.
  • Schrödinger: Public computational chemistry platform offering physics-based molecular simulation and drug design software. Directly comparable as the established 'complex tools' competitor named explicitly on Pauling.AI's comparison page, serving the same pharma/biotech customers with overlapping workflow tooling.
  • BenevolentAI: AI drug discovery company applying machine learning to biomedical knowledge graphs and target identification. Comparable as another end-to-end AI pharma company pursuing the same thesis of compressing the early drug discovery funnel through automation.
  • Insilico Medicine: AI-driven drug discovery company combining generative chemistry, target discovery, and clinical development. Comparable as one of the most well-funded end-to-end AI drug discovery competitors pursuing the same 'compressed timelines' thesis with much larger capital and longer operating history.
  • Recursion Pharmaceuticals: AI-native drug discovery company combining high-throughput biology with machine learning across a broader phenotypic and target-based discovery footprint. Comparable as a competing AI drug discovery platform with significantly more capital and pipeline depth.

Broad incumbents

  • Isomorphic Labs: Alphabet/DeepMind-backed drug discovery company leveraging AlphaFold and related foundation models. Comparable as a well-capitalized AI drug discovery competitor that Pauling.AI's stack explicitly integrates (AlphaFold, Boltz/DiffDock are included as workflow components).

Emerging players

  • Crēdo Science: Emerging AI-native drug discovery platforms building workflow automation around generative biology and chemistry models — comparable as a similarly-staged early entrant in the same 'AI workflow for scientists' category as Pauling.AI.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat3 records

Key risks6 records

Key highlights6 records

Customer concentration

Pauling social profiles

Digital presence

Pauling financial estimates

Financial estimate

Revenue estimate

Valuation estimate

Pauling leadership team

Management profile

Number of profiles

Pauling funding detail

Funding detail

Funding overview

Funding rounds1 record

Investors1 record

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

Pauling M&A and investment

M&A and investment

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Pauling

What does Pauling do?

Pauling.AI operates the Autochem platform, a fully autonomous drug discovery system that lets users describe a protein target (e.g., '6VC8') in plain language and then automatically orchestrates molecular docking, molecular dynamics (GROMACS), ADMET prediction, and quality control to deliver validated drug candidates in days. The platform sells both standardized hit screening services (e.g., 10M-compound docking + MD validation for $10,000) and enterprise-grade platform access tailored to pharmaceutical, biotech, academic, and longevity research customers.

Is Pauling a public or private company?

Pauling is a private company. It is classified as venture growth investor backed and is currently operating.

When was Pauling founded?

Pauling was founded in 2024. It employs 1 to 10 people.

Where is Pauling based?

Pauling is headquartered in Boston, United States, in the North America region.

How does Pauling make money?

Two revenue lines are on record. Project-Based Drug Discovery Services are the primary driver. The others are enterprise Platform Access.

Who are Pauling's main competitors?

Direct peers on record are XtalPi, Atomwise, Iambic Therapeutics, Exscientia, Schrödinger, BenevolentAI, Insilico Medicine and Recursion Pharmaceuticals. Isomorphic Labs is listed as a broad incumbent. Crēdo Science is listed as an emerging player.

Does Pauling have an API?

No public API is recorded for Pauling.

What industry is Pauling in?

Pauling's product category is AI Drug Discovery Platform. Its primary akta.pro industry code is HLAGAJAO, AI/ML Platforms for Drug Discovery & Experiment Optimization, with a secondary code of HLAAAIAE, AI/ML-Enabled Biologic Discovery Platforms (computational design, in silico screening). Its NAICS code is 541714 and its SIC code is 7372.

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