Developer docs
API playgroundTry for free, no card

Search company profiles

Knowledgator Engineering

Full company profile

uuid0003o21

Namestring
Knowledgator Engineering
Legal namestring
Knowledgator Engineering
Company typeenum
Private
Founded yearint
2023
Operating statusenum
Operating
Ownership categoryenum
Headcount rangeband
1–10
akta.pro rankint
HeadquartersLondon, United Kingdom
HQ citystring
London
HQ countrystring
United Kingdom
HQ regionstring
Europe
Markets served

Serves global market

Keyword5 values
Named Entity Recognition, Information Extraction, Zero-Shot Text Classification, Open-Source NLP Models, Knowledge Graph Retrieval
Industry5 codes
1Text Analytics & Information Extraction (NER, classification, sentiment)
CodeHDAAADAAPrimaryYes
2OCR, ICR & Intelligent Document Processing (IDP)
CodeBPAAAKABPrimaryNo
3Search, Retrieval & Semantic Ranking (BM25/vector, hybrid)
CodeHDAAADABPrimaryNo
4Data Discovery, Classification & Labeling
CodeHDADAFAFPrimaryNo
5Bioinformatics & Multi-omics Analysis Software
CodeHLAGAJADPrimaryNo
NAICS code1 code
  • Software Publishers513210
SIC code1 code
  • Services-Computer Programming, Data Processing, Etc.7370
Product category
Natural Language Processing / AI Information Extraction
GTM motion2 records

Each record includes

Type, Description, Source

Revenue model4 records
1Platform Subscription/Tiered Plans
TypeSubscription Recurring
Description

SaaS platform with multiple subscription tiers ranging from individual developers to enterprise-scale deployments. Free credits provided for initial exploration. Customized plans available for high-volume or specialized requirements.

knowledgator.com
2Usage-Based API Access
TypeUsage Based
Description

Pay-per-use model for API access, with inference credits consumed based on volume. Supports pay-as-you-go and monthly billing options.

knowledgator.com
3Enterprise Consulting Services
TypeProfessional Services
Description

Consultation with team for unique use cases, custom integrations, and specialized deployment requirements.

knowledgator.com
4Open-Source Models (Freemium)
TypeFreemium
Description

Core open-source models available for free download and local deployment, with paid cloud platform access for those preferring managed infrastructure.

knowledgator.com
Marketing channels10 records

Each record includes

Title, Type, Stage, Description, Source

Distribution channels4 records

Each record includes

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

Cost components5 values
Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations
Pricing details3 tiers
1Free trial with credits for platform exploration
ModelFreemiumBilling cadencePay-as-you-go
Notes

New users receive free credits to explore the full pipeline from model selection through fine-tuning to local deployment.

knowledgator.com
2Tiered plans for individuals to enterprise
ModelSubscriptionBilling cadenceMonthly
Notes

Multiple plans available from individual developers to enterprise-scale deployments. Details at platform.knowledgator.com/plans.

knowledgator.com
3Enterprise custom pricing
ModelSubscriptionBilling cadenceAnnual
Notes

Customized plans for high-volume or specialized requirements. Contact sales via Calendly booking.

knowledgator.com
GTM typeB2B
B2B
Offering typeSoftware
Software
Brand1 of 6 records shown
1GLiNER
Description

Efficient zero-shot Named Entity Recognition (NER) models for extracting entities from text.

knowledgator.com
+5 more records
Core offering1 text field

Knowledgator Engineering builds and distributes open-source AI/NLP models and a commercial SaaS platform that extract structured data (entities, relationships, classifications, JSON) from unstructured text using a non-generative approach with sub-second latency. The portfolio centers on the GLiNER zero-shot Named Entity Recognition family, the GLiClass zero-shot text classification family, Extract-It relation extraction, Text2Json structured output conversion, RetriCo knowledge graph retrieval, and specialized variants (multilingual, biomedical, PII detection). The Knowledgator Platform wraps these into a managed service offering fine-tuning, hardware optimization, and one-click deployment for enterprise buyers.

Differentiator
Functional benefit
Problem solved
Quantifiable outcome1 of 5 values shown
  • 98% F1 score on PII detection in Electronic Health Records vs 22.3% for Llama and 50.2% for Azure Presidio
+4 more records
Product overview1 text field

Knowledgator Engineering offers an open-source AI platform for information extraction, comprising multiple specialized products that work together as both open-source frameworks and a commercial platform. At its core, the platform is powered by GLiNER (zero-shot Named Entity Recognition) and GLiClass (zero-shot text classification), supplemented by Extract-It (relation extraction), Text2Json (text-to-structured-JSON), GLinker (entity linking for knowledge base connections), RetriCo (knowledge graph framework for building and querying RAG systems), LiqFit (few-shot fine-tuning), and Chemical Converter (chemical format translation). The commercial Knowledgator Platform wraps these open-source models into a unified SaaS offering, providing API access, fine-tuning, hardware optimization (quantization/pruning/distillation), and one-click deployment across on-premises, private cloud, and edge environments — all delivering structured JSON output at sub-second latency. Specialized variants target specific verticals: GLiNER-X (multilingual, 20+ languages), GLiNER-PII (privacy/PII detection), and GLiNER-BioMed (biomedical domain, developed with University of Geneva). The platform collectively reports over 5 million model downloads on Hugging Face.

Product and service14 records
1Knowledgator Platform
CategoryAI/NLP Platform (SaaS)
Description

All-in-one commercial SaaS for optimizing AI models for edge and on-premise deployment: fine-tune open-source models, optimize them for any hardware (quantization, pruning, distillation), and ship to on-prem, private cloud, or edge environments through a single interface with API access and multiple pricing tiers.

2GLiNER
CategoryOpen-Source NLP Model
Description

Open-source zero-shot Named Entity Recognition model family that detects and classifies entities such as people, organizations, locations, dates, monetary values, and custom user-defined types across multiple languages, with specialized variants (bi-encoder, multilingual, biomedical, PII).

3GLiClass
CategoryOpen-Source NLP Model
Description

Open-source zero-shot text classification model family that categorizes documents, paragraphs, or sentences into any label set without fine-tuning, supporting multi-label classification, topic categorization, sentiment analysis, content moderation, and customer-intent classification.

4Extract-It
CategoryOpen-Source NLP Model
Description

Relation extraction model that maps how entities are connected (e.g., which gene regulates another gene) and automatically constructs knowledge graphs, integrated into the unified Knowledgator pipeline alongside NER and classification.

5Text2Json
CategoryOpen-Source NLP Model
Description

Text-to-structured-JSON conversion capability that transforms free-text input (invoices, contracts, clinical notes, financial filings) into clean, schema-conforming JSON suitable for databases, APIs, and downstream enterprise systems.

6GLinker
CategoryOpen-Source NLP Framework
Description

Open-source entity linking framework with a layered pipeline (L1 NER, L2 candidate retrieval via dictionary exact/fuzzy matching, L3 disambiguation via linker model, L0 aggregation) that connects extracted entities to knowledge bases, hospital systems, medication formularies, and terminology catalogs.

7RetriCo
CategoryOpen-Source Framework
Description

Open-source knowledge graph framework for building, querying, and managing knowledge graphs, with a tool-calling layer that lets LLM agents issue structured function calls translated into parameterized Cypher queries, and supports graph database backends, community detection, and KG embeddings.

8Chemical Converter
CategorySpecialized Open-Source Model
Description

Specialized open-source model collection that translates between different chemical naming and structure formats (e.g., chemical name ↔ standard chemistry interchange formats) for life-sciences and chemistry workflows.

9LiqFit
CategoryOpen-Source Framework
Description

Open-source few-shot learning framework for fine-tuning Knowledgator models with minimal labeled data, achieving results comparable to supervised models that require 10–100x more training examples.

10GLiNER-X (Multilingual)
CategorySpecialized Open-Source Model
Description

Multilingual Named Entity Recognition model built on MT5 encoder architecture supporting 20+ languages (Swedish, Norwegian, Czech, Polish, Lithuanian, Estonian, Latvian, Spanish, Finnish, English, German, French, Romanian, Italian, Portuguese, Dutch, Ukrainian, Hindi, Chinese, Arabic) in three model sizes.

11GLiNER-PII
CategorySpecialized Open-Source Model
Description

Production-grade model for detecting personally identifiable information (PII), protected health information (PHI), and payment card industry (PCI) data across 60+ predefined categories, supporting HIPAA, PCI-DSS, and GDPR compliance workflows.

12GLiNER-BioMed
CategorySpecialized Open-Source Model
Description

Biomedical Named Entity Recognition model family developed in collaboration with the DS4DH research group at the University of Geneva, leveraging synthetic annotations distilled from large generative biomedical language models to deliver zero-shot and few-shot biomedical entity recognition in six model sizes.

13GLiNER Multi-task Large Model v0.5
CategorySpecialized Open-Source Model
Description

Multi-task NER model specialized for invoice data extraction, capturing invoice numbers, dates, due dates, vendor and customer names/addresses, line items (description, quantity, unit price, line total), subtotal, tax rate, tax amount, and total, with export to QuickBooks, Xero, and Sage accounting systems.

14knowledgator-pipeline
CategoryAI/NLP Platform (SaaS)
Description

Core workflow engine of the Knowledgator Platform orchestrating a four-step pipeline: select a task-specific model (GLiNER, GLiClass, Encoders), fine-tune on domain data with minimal examples, optimize via quantization/pruning/distillation, and deploy to on-prem, private cloud, or edge with one click at sub-50ms inference.

Scale indicator7 records

Each record includes

Type, Value, Description, Source

Partnership1 partner
1DS4DH (University of Geneva)
Strategic tierCoreTypeStrategic or Co-development Partner
Description

Collaboration with DS4DH research group from University of Geneva for developing GLiNER-BioMed specialized biomedical NER models. The partnership leverages synthetic annotations distilled from large generative biomedical language models to achieve state-of-the-art zero-shot and few-shot performance in biomedical entity recognition tasks.

docs.knowledgator.com
Recent move6 records

Each record includes

Date, Type, Title, Description, Source

Expansion highlight6 records

Each record includes

Type, Description

Peers10 records
TypeDirect peer
Description

Hugging Face is the primary open-source hub for transformer models including NER, classification, and information extraction. Knowledgator publishes its models on Hugging Face and competes for the same developer mindshare in open-source NLP.

TypeDirect peer
Description

John Snow Labs provides enterprise-grade biomedical and clinical NLP models with HIPAA-grade deployment, directly competing with GLiNER-BioMed in the healthcare vertical.

TypeDirect peer
Description

spaCy is the leading open-source industrial-strength NLP library for NER, classification, and information extraction. It is a foundational alternative to Knowledgator's GLiNER/GLiClass for developers building extraction pipelines.

4Azure AI Language (Microsoft)
TypeBroad incumbent
Description

Azure AI Language is a hyperscaler NLP service offering NER, PII detection, sentiment, and text analytics. It is a named competitor in Knowledgator's PII benchmarks (50.2% F1) and competes for enterprise extraction workloads.

TypeBroad incumbent
Description

Amazon Comprehend is AWS's managed NLP service covering entity recognition, PII detection, and document classification. It is a broad incumbent competing for the same enterprise extraction workloads as Knowledgator's commercial platform.

TypeBroad incumbent
Description

Google Cloud's Natural Language API provides entity analysis, classification, and custom NLP within the broader Google Cloud ecosystem. It is a broad incumbent alternative, particularly relevant given Knowledgator's undisclosed Google investment.

TypeEmerging player
Description

Cohere provides enterprise NLP APIs for classification, NER, and retrieval. It targets similar enterprise extraction workloads with a managed cloud model rather than Knowledgator's open-source / on-prem approach.

TypeEmerging player
Description

Snorkel AI focuses on data-centric AI with weak supervision and programmatic labeling for enterprise NLP. It overlaps with Knowledgator's few-shot/LiqFit positioning and its target buyer of enterprise data teams.

TypeEmerging player
Description

Primer.ai provides enterprise NLP and knowledge extraction for government, finance, and intelligence customers. It is a comparable specialist in information extraction with a strong on-prem / air-gapped deployment posture.

TypeEmerging player
Description

Scale AI is a data-centric AI company with adjacent capabilities in labeling, evaluation, and fine-tuning. It overlaps with Knowledgator's LiqFit few-shot fine-tuning and data-advantage positioning.

Market position
Strengths4 records

Each record includes

Headline, Details, Source

Weaknesses4 records

Each record includes

Headline, Details, Source

Competitive moat5 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

Segment5 records

Each record includes

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

Ideal customer profile2 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
Yes

Docs URL, Description

Integration8 records

Each record includes

Title, Type, Description, Source

AI capability5 records

Each record includes

Type, Description, Source

AI maturity
App detail

Has app

Feature13 records

Each record includes

Title, Differentiator, Description, Source

Core technology
Revenue estimate
Valuation estimate
Number of profiles
Profiles3 records

Each record includes

Name, Designation, Designation category, Overview, Profile commentary, Source

No data
Compliance3 records

Each record includes

Name, Class, Description

Funding overview

Funding stage, Last funding date, Total funding USD

Funding rounds5 records

Each record includes

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

Investors3 records

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 →

Knowledgator Engineering

Natural Language Processing / AI Information Extractionknowledgator.com

Knowledgator Engineering firmographics

Firmographics
Name
Knowledgator Engineering
Legal name
Knowledgator Engineering
Website
https://knowledgator.com
Company type
Private
Founded year
2023
Operating status
Operating
Headcount range
1–10 employees
Ownership category
akta.pro rank

Knowledgator Engineering industry classification

Industry
Product category
Natural Language Processing / AI Information Extraction
NAICS
Software Publishers (513210)
SIC
Services-Computer Programming, Data Processing, Etc. (7370)
akta.pro primary industry
Text Analytics & Information Extraction (NER, classification, sentiment) (HDAAADAA)
akta.pro secondary industries
OCR, ICR & Intelligent Document Processing (IDP) (BPAAAKAB), Search, Retrieval & Semantic Ranking (BM25/vector, hybrid) (HDAAADAB), Data Discovery, Classification & Labeling (HDADAFAF), Bioinformatics & Multi-omics Analysis Software (HLAGAJAD)

Keywords

  • Named Entity Recognition
  • Information Extraction
  • Zero-Shot Text Classification
  • Open-Source NLP Models
  • Knowledge Graph Retrieval

Where Knowledgator Engineering is headquartered

Location

Headquarters

HQ city
London
HQ country
United Kingdom
HQ region
Europe

Markets served

Knowledgator Engineering business model

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

Revenue model

  1. Platform Subscription/Tiered Plans: SaaS platform with multiple subscription tiers ranging from individual developers to enterprise-scale deployments. Free credits provided for initial exploration. Customized plans available for high-volume or specialized requirements.
  2. Usage-Based API Access: Pay-per-use model for API access, with inference credits consumed based on volume. Supports pay-as-you-go and monthly billing options.
  3. Enterprise Consulting Services: Consultation with team for unique use cases, custom integrations, and specialized deployment requirements.
  4. Open-Source Models (Freemium): Core open-source models available for free download and local deployment, with paid cloud platform access for those preferring managed infrastructure.

Pricing tiers

ModelBillingPrice
FreemiumPay-as-you-goFree trial with credits for platform exploration
SubscriptionMonthlyTiered plans for individuals to enterprise
SubscriptionAnnualEnterprise custom pricing

Go-to-market motion2 records

Distribution channels4 records

Marketing channels10 records

Knowledgator Engineering product offering

Product offering

Core offering

Knowledgator Engineering builds and distributes open-source AI/NLP models and a commercial SaaS platform that extract structured data (entities, relationships, classifications, JSON) from unstructured text using a non-generative approach with sub-second latency. The portfolio centers on the GLiNER zero-shot Named Entity Recognition family, the GLiClass zero-shot text classification family, Extract-It relation extraction, Text2Json structured output conversion, RetriCo knowledge graph retrieval, and specialized variants (multilingual, biomedical, PII detection). The Knowledgator Platform wraps these into a managed service offering fine-tuning, hardware optimization, and one-click deployment for enterprise buyers.

Product overview

Knowledgator Engineering offers an open-source AI platform for information extraction, comprising multiple specialized products that work together as both open-source frameworks and a commercial platform. At its core, the platform is powered by GLiNER (zero-shot Named Entity Recognition) and GLiClass (zero-shot text classification), supplemented by Extract-It (relation extraction), Text2Json (text-to-structured-JSON), GLinker (entity linking for knowledge base connections), RetriCo (knowledge graph framework for building and querying RAG systems), LiqFit (few-shot fine-tuning), and Chemical Converter (chemical format translation). The commercial Knowledgator Platform wraps these open-source models into a unified SaaS offering, providing API access, fine-tuning, hardware optimization (quantization/pruning/distillation), and one-click deployment across on-premises, private cloud, and edge environments — all delivering structured JSON output at sub-second latency. Specialized variants target specific verticals: GLiNER-X (multilingual, 20+ languages), GLiNER-PII (privacy/PII detection), and GLiNER-BioMed (biomedical domain, developed with University of Geneva). The platform collectively reports over 5 million model downloads on Hugging Face.

Differentiator

Problem solved

Functional benefit

Brands

  • GLiNER: Efficient zero-shot Named Entity Recognition (NER) models for extracting entities from text.
  • GLiClass
  • GLiNKER
  • LiqFit
  • RetriCo
  • Chemical Converter

Products and services

  • Knowledgator Platform All-in-one commercial SaaS for optimizing AI models for edge and on-premise deployment: fine-tune open-source models, optimize them for any hardware (quantization, pruning, distillation), and ship to on-prem, private cloud, or edge environments through a single interface with API access and multiple pricing tiers.
  • GLiNER Open-source zero-shot Named Entity Recognition model family that detects and classifies entities such as people, organizations, locations, dates, monetary values, and custom user-defined types across multiple languages, with specialized variants (bi-encoder, multilingual, biomedical, PII).
  • GLiClass Open-source zero-shot text classification model family that categorizes documents, paragraphs, or sentences into any label set without fine-tuning, supporting multi-label classification, topic categorization, sentiment analysis, content moderation, and customer-intent classification.
  • Extract-It Relation extraction model that maps how entities are connected (e.g., which gene regulates another gene) and automatically constructs knowledge graphs, integrated into the unified Knowledgator pipeline alongside NER and classification.
  • Text2Json Text-to-structured-JSON conversion capability that transforms free-text input (invoices, contracts, clinical notes, financial filings) into clean, schema-conforming JSON suitable for databases, APIs, and downstream enterprise systems.
  • GLinker Open-source entity linking framework with a layered pipeline (L1 NER, L2 candidate retrieval via dictionary exact/fuzzy matching, L3 disambiguation via linker model, L0 aggregation) that connects extracted entities to knowledge bases, hospital systems, medication formularies, and terminology catalogs.
  • RetriCo Open-source knowledge graph framework for building, querying, and managing knowledge graphs, with a tool-calling layer that lets LLM agents issue structured function calls translated into parameterized Cypher queries, and supports graph database backends, community detection, and KG embeddings.
  • Chemical Converter Specialized open-source model collection that translates between different chemical naming and structure formats (e.g., chemical name ↔ standard chemistry interchange formats) for life-sciences and chemistry workflows.
  • LiqFit Open-source few-shot learning framework for fine-tuning Knowledgator models with minimal labeled data, achieving results comparable to supervised models that require 10–100x more training examples.
  • GLiNER-X (Multilingual) Multilingual Named Entity Recognition model built on MT5 encoder architecture supporting 20+ languages (Swedish, Norwegian, Czech, Polish, Lithuanian, Estonian, Latvian, Spanish, Finnish, English, German, French, Romanian, Italian, Portuguese, Dutch, Ukrainian, Hindi, Chinese, Arabic) in three model sizes.
  • GLiNER-PII Production-grade model for detecting personally identifiable information (PII), protected health information (PHI), and payment card industry (PCI) data across 60+ predefined categories, supporting HIPAA, PCI-DSS, and GDPR compliance workflows.
  • GLiNER-BioMed Biomedical Named Entity Recognition model family developed in collaboration with the DS4DH research group at the University of Geneva, leveraging synthetic annotations distilled from large generative biomedical language models to deliver zero-shot and few-shot biomedical entity recognition in six model sizes.
  • GLiNER Multi-task Large Model v0.5 Multi-task NER model specialized for invoice data extraction, capturing invoice numbers, dates, due dates, vendor and customer names/addresses, line items (description, quantity, unit price, line total), subtotal, tax rate, tax amount, and total, with export to QuickBooks, Xero, and Sage accounting systems.
  • knowledgator-pipeline Core workflow engine of the Knowledgator Platform orchestrating a four-step pipeline: select a task-specific model (GLiNER, GLiClass, Encoders), fine-tune on domain data with minimal examples, optimize via quantization/pruning/distillation, and deploy to on-prem, private cloud, or edge with one click at sub-50ms inference.

Quantifiable outcome

  • 98% F1 score on PII detection in Electronic Health Records vs 22.3% for Llama and 50.2% for Azure Presidio
  • +4 more outcomes

Companies that use Knowledgator Engineering

Customer profile

Segments5 records

Ideal customer profiles2 records

Knowledgator Engineering technology and API

Technology

Technology focussed Yes

API detail

Has API
Yes
API docs
API detail

Core technology

AI maturity

App detail

Integration8 records

AI capability5 records

Feature13 records

Knowledgator Engineering partnerships and signals

Strategic signal

Partnerships

One partnership is on record.

  • DS4DH (University of Geneva)coreStrategic or Co-development PartnerCollaboration with DS4DH research group from University of Geneva for developing GLiNER-BioMed specialized biomedical NER models. The partnership leverages synthetic annotations distilled from large generative biomedical language models to achieve state-of-the-art zero-shot and few-shot performance in biomedical entity recognition tasks.

Scale indicators7 records

Recent moves6 records

Expansion highlights6 records

Knowledgator Engineering competitors and assessment

Company assessment

Direct peers

  • Hugging Face: Hugging Face is the primary open-source hub for transformer models including NER, classification, and information extraction. Knowledgator publishes its models on Hugging Face and competes for the same developer mindshare in open-source NLP.
  • John Snow Labs: John Snow Labs provides enterprise-grade biomedical and clinical NLP models with HIPAA-grade deployment, directly competing with GLiNER-BioMed in the healthcare vertical.
  • spaCy: spaCy is the leading open-source industrial-strength NLP library for NER, classification, and information extraction. It is a foundational alternative to Knowledgator's GLiNER/GLiClass for developers building extraction pipelines.

Broad incumbents

  • Azure AI Language (Microsoft): Azure AI Language is a hyperscaler NLP service offering NER, PII detection, sentiment, and text analytics. It is a named competitor in Knowledgator's PII benchmarks (50.2% F1) and competes for enterprise extraction workloads.
  • Amazon Comprehend: Amazon Comprehend is AWS's managed NLP service covering entity recognition, PII detection, and document classification. It is a broad incumbent competing for the same enterprise extraction workloads as Knowledgator's commercial platform.
  • Google Cloud Natural Language API: Google Cloud's Natural Language API provides entity analysis, classification, and custom NLP within the broader Google Cloud ecosystem. It is a broad incumbent alternative, particularly relevant given Knowledgator's undisclosed Google investment.

Emerging players

  • Cohere: Cohere provides enterprise NLP APIs for classification, NER, and retrieval. It targets similar enterprise extraction workloads with a managed cloud model rather than Knowledgator's open-source / on-prem approach.
  • Snorkel AI: Snorkel AI focuses on data-centric AI with weak supervision and programmatic labeling for enterprise NLP. It overlaps with Knowledgator's few-shot/LiqFit positioning and its target buyer of enterprise data teams.
  • Primer.ai: Primer.ai provides enterprise NLP and knowledge extraction for government, finance, and intelligence customers. It is a comparable specialist in information extraction with a strong on-prem / air-gapped deployment posture.
  • Scale AI: Scale AI is a data-centric AI company with adjacent capabilities in labeling, evaluation, and fine-tuning. It overlaps with Knowledgator's LiqFit few-shot fine-tuning and data-advantage positioning.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks6 records

Key highlights6 records

Customer concentration

Knowledgator Engineering social profiles

Digital presence

Knowledgator Engineering compliance and trust

Trust signal

Compliance3 records

Knowledgator Engineering financial estimates

Financial estimate

Revenue estimate

Valuation estimate

Knowledgator Engineering leadership team

Management profile

Number of profiles

Profiles3 records

Knowledgator Engineering funding detail

Funding detail

Funding overview

Funding rounds5 records

Investors3 records

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

Knowledgator Engineering 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 Knowledgator Engineering

What does Knowledgator Engineering do?

Knowledgator Engineering builds and distributes open-source AI/NLP models and a commercial SaaS platform that extract structured data (entities, relationships, classifications, JSON) from unstructured text using a non-generative approach with sub-second latency. The portfolio centers on the GLiNER zero-shot Named Entity Recognition family, the GLiClass zero-shot text classification family, Extract-It relation extraction, Text2Json structured output conversion, RetriCo knowledge graph retrieval, and specialized variants (multilingual, biomedical, PII detection). The Knowledgator Platform wraps these into a managed service offering fine-tuning, hardware optimization, and one-click deployment for enterprise buyers.

Is Knowledgator Engineering a public or private company?

Knowledgator Engineering is a private company. It is classified as founder individual operated bootstrapped and is currently operating.

When was Knowledgator Engineering founded?

Knowledgator Engineering was founded in 2023. It employs 1 to 10 people.

Where is Knowledgator Engineering based?

Knowledgator Engineering is headquartered in London, United Kingdom, in the Europe region.

How does Knowledgator Engineering make money?

Four revenue lines are on record. Platform Subscription/Tiered Plans are the primary driver. The others are usage-Based API Access, enterprise Consulting Services and open-Source Models (Freemium).

Who are Knowledgator Engineering's main competitors?

Direct peers on record are Hugging Face, John Snow Labs and spaCy. Broad incumbents are Azure AI Language (Microsoft), Amazon Comprehend and Google Cloud Natural Language API. Emerging players are Cohere, Snorkel AI, Primer.ai and Scale AI.

Does Knowledgator Engineering have an API?

Yes. Knowledgator provides public-facing APIs enabling developers to build and automate information extraction pipelines. The API is used within the Knowledgator platform and is available via the platform at platform.knowledgator.com. Developers can chain APIs to compose multi-step pipelines (NER → Relation Extraction → Classification), with every model outputting clean JSON ready for downstream systems. Sub-second latency is achieved for full multi-step pipelines. Documentation and code examples are available in Python, JavaScript, and TypeScript. The RetriCo framework also exposes LLM tool-use capabilities via structured function calls, with graph query tools (search_entity, list_entities, get_entity_relations, get_neighbors, get_subgraph, get_chunks_for_entity, find_shortest_path) translated into parameterized Cypher queries. Developer documentation is at docs.knowledgator.com.

What industry is Knowledgator Engineering in?

Knowledgator Engineering's product category is Natural Language Processing / AI Information Extraction. Its primary akta.pro industry code is HDAAADAA, Text Analytics & Information Extraction (NER, classification, sentiment), with a secondary code of BPAAAKAB, OCR, ICR & Intelligent Document Processing (IDP). Its NAICS code is 513210 and its SIC code is 7370.

Unlock the full company data

50 free credits on sign-up, no credit card required.

Contact sales
Live signals