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Invisible Technologies

  • What it is:Invisible Technologies is an AI software platform that structures enterprise data, builds digital workflows, deploys AI agents, and integrates human expertise to make generative AI work effectively in real-world business operations.
  • Best for:Frontier AI labs and model builders, Regulated industries needing compliant AI, Enterprises with complex operational data
  • Pricing:Starting from $30–$45/hour
  • Rating:92/100Excellent
  • Expert's conclusion:Invisible excels for elite AI teams that require rapid, expert powered data annotation at research speeds, however, they require an enterprise commitment.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Invisible Technologies and What Does It Do?

Invisible Technologies is a proprietary AI software platform developed for large enterprises, which organizes disorganized data into structured data, develops digital workflows, implements agentic solutions and utilizes human experts to enable large-scale operationalization of AI within organizations. Over 80% of the largest AI model providers including Cohere, Microsoft and AWS have utilized Invisible Technologies' training of their foundation models. For over five years, Invisible Technologies has been profitable as well as providing AI-based solutions to both public and private sector organizations with real-world uses of AI.

Active
📍San Francisco, CA
📅Founded 2015
🏢Private
TARGET SEGMENTS
EnterprisePublic SectorRetailDefenseSports

What Are Invisible Technologies's Key Business Metrics?

💵
$134M
Revenue (2024)
💵
2x+
Revenue Growth 2023-2024
💵
24x
Revenue Growth 2020-2023
📊
$144M
Total Funding
📊
$2B+
Valuation
📊
#152 overall, #2 AI company
Inc. 5000 Ranking
👥
Microsoft, SAIC, Swiss Gear, Charlotte Hornets
Customers

How Credible and Trustworthy Is Invisible Technologies?

92/100
Excellent

A proven and established unicorn over $2 billion with exponential growth, prominent enterprise clients and investment from credible sources demonstrates high credibility.

BREAKDOWN
Product Maturity95/100
Company Stability98/100
Security & Compliance85/100
User Reviews80/100
Transparency90/100
Support Quality88/100
TRUST SIGNALS
Profitable for 5+ years$2B+ unicorn valuationTrained 80% of world's LLMsCustomers include Microsoft, US Navy partners#2 fastest growing AI company Inc. 5000$144M total funding

What is the history of Invisible Technologies and its key milestones?

2015

Company Founded

Invisible Technologies was founded by Francis Pedraza, who initially focused on developing data services for small businesses.

2020

Hypergrowth Begins

As Invisible Technologies shifted its focus to enterprise-level clients and improved operational processes, the organization experienced a 24-fold increase in revenue from 2020 to 2023.

2023

$134M Revenue Milestone

Of the $134 million in annual revenue earned by Invisible Technologies from 2023, the majority ($132 million) were earned through engineering and operational efforts, while only $2 million were spent on sales efforts.

2024

Inc. 5000 #2 AI Company

Based upon the Inc. 5000 list released in 2024, Invisible Technologies ranked as the #2 fastest-growing AI company and the #152 fastest-growing company overall. In addition, according to this same list, Invisible Technologies doubled its revenue from 2023 to 2024.

2025

$100M Growth Funding

In April 2024, Invisible Technologies secured a $100 million investment from Vanara Capital, increasing the company's total value to $144 million and establishing the company as a unicorn a privately held company valued at over $1 billion. The valuation of Invisible Technologies at over $2 billion confirms that it has reached unicorn status.

2025

Global Expansion

Following the $100 million investment from Vanara Capital, Invisible Technologies opened new offices in New York City, San Francisco, Washington D.C., and London and expanded its engineering staff to approximately 350 employees. At the time of the investment, Matthew Fitzpatrick replaced Francis Pedraza as CEO.

What Are the Key Features of Invisible Technologies?

📊
End-to-End AI Platform
Invisible Technologies enables organizations to organize and clean their disorganized data, build digital workflows, deploy agentic solutions and measure the performance of their AI initiatives.
✨
Data Organization & Labeling
By organizing, cleaning, labeling and mapping an organization's data, Invisible Technologies enables the organization to deploy AI models in production.
✨
Expert Marketplace
Invisible Technologies provides the technology necessary to combine the appropriate human experts with software solutions to assist organizations in solving complex organizational problems.
✨
Agentic Workflows
Using its AI software platform, Invisible Technologies enables the creation of autonomous AI agents that are able to perform real-world business workflows across legacy systems used by organizations.
✨
Multi-Industry Customization
The AI software platform offered by Invisible Technologies allows organizations to customize AI solutions to meet the needs of any specific industry, function or use case such as retail, financial institutions or military defense.
✨
Foundation Model Training
According to Invisible Technologies, the company's LLMs have been trained for 80% of the world's largest AI model providers including Cohere, Microsoft and AWS.

What Technology Stack and Infrastructure Does Invisible Technologies Use?

Infrastructure

Multi-region cloud with offices in NY, SF, DC, London

Integrations

Legacy enterprise systemsMicrosoft ecosystemAWSCohere AI models

AI/ML Capabilities

Proprietary platform combining cutting-edge AI software with human expertise; trained foundation models for 80% of top global AI providers; enables agentic workflows on 20+ year old enterprise software

Inferred from enterprise focus, legacy system integration capability, and foundation model training expertise

What Are the Best Use Cases for Invisible Technologies?

Enterprise Data Teams
Invisible Technologies enables organizations to structure and unify their messy enterprise data, thereby allowing them to deploy AI models and measure ROI across legacy systems.
Public Sector & Defense
Develop AI enabled simulation models and autonomous decision making models as shown in SAIC/U.S. Navy UUV Exercises
Retail & Supply Chain
Use data structuring to enhance demand forecasting and provide better supply chain transparency as done for Swiss Gear
Sports Analytics
Use AI data analysis to validate draft pick choices and improve daily operational efficiency as done for Charlotte Hornets
NOT FORIndividual Developers
This enterprise focused platform does not have a design for individual or small team use; scale is too large for this type of application
NOT FORReal-time High Frequency Trading
The data infrastructure focus of this platform will not allow for the sub-millisecond latency requirements of High Frequency Trading

How Much Does Invisible Technologies Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
RLHF Services$30–$45/hourCharges to model labs for reinforcement learning with human feedback, model output scoring, ranking, and reasoning annotationSacra research
Rater Compensation$15–$20/hourPayment to trained raters in global workforce for annotation and evaluation workSacra research
Enterprise AI TrainingCustom quoteFull-stack AI training partnerships for regulated industries (healthcare, finance, defense) with vertical-specific RLHF products—
Data Labeling & AnnotationCustom quoteExpert-annotated data for model training, stress-testing AI systems, and edge case handling—
RLHF Services$30–$45/hour
Charges to model labs for reinforcement learning with human feedback, model output scoring, ranking, and reasoning annotation
Sacra research
Rater Compensation$15–$20/hour
Payment to trained raters in global workforce for annotation and evaluation work
Sacra research
Enterprise AI TrainingCustom quote
Full-stack AI training partnerships for regulated industries (healthcare, finance, defense) with vertical-specific RLHF products
Data Labeling & AnnotationCustom quote
Expert-annotated data for model training, stress-testing AI systems, and edge case handling

How Does Invisible Technologies Compare to Competitors?

FeatureInvisible TechnologiesScale AIMercor
2024 Revenue$134M$1.5B$50M
Revenue Growth (YoY)123%97%4900%
Primary FocusRLHF & expert annotationGeneral data labelingAI data labeling
Enterprise PositioningRegulated industries (healthcare, finance, defense)Broad enterpriseAI-native startups
Pricing ModelHourly rates ($30-$45/hour to labs)Per-label + contracts ($93K-$400K/year)
Key ClientsMicrosoft, Cohere, Mistral, AI21, PerplexityBroad enterprise baseFrontier AI labs
Workforce Size3000+ global ratersVendor staffing
Valuation/MultipleEstimated $1B+ implied$25B (16.7x multiple)$2B (40x multiple)
SpecializationReasoning tasks & RLHFGeneral labelingAI-native workflows
2024 Revenue
Invisible Technologies$134M
Scale AI$1.5B
Mercor$50M
Revenue Growth (YoY)
Invisible Technologies123%
Scale AI97%
Mercor4900%
Primary Focus
Invisible TechnologiesRLHF & expert annotation
Scale AIGeneral data labeling
MercorAI data labeling
Enterprise Positioning
Invisible TechnologiesRegulated industries (healthcare, finance, defense)
Scale AIBroad enterprise
MercorAI-native startups
Pricing Model
Invisible TechnologiesHourly rates ($30-$45/hour to labs)
Scale AIPer-label + contracts ($93K-$400K/year)
Mercor—
Key Clients
Invisible TechnologiesMicrosoft, Cohere, Mistral, AI21, Perplexity
Scale AIBroad enterprise base
MercorFrontier AI labs
Workforce Size
Invisible Technologies3000+ global raters
Scale AIVendor staffing
Mercor—
Valuation/Multiple
Invisible TechnologiesEstimated $1B+ implied
Scale AI$25B (16.7x multiple)
Mercor$2B (40x multiple)
Specialization
Invisible TechnologiesReasoning tasks & RLHF
Scale AIGeneral labeling
MercorAI-native workflows

How Does Invisible Technologies Compare to Competitors?

vs Scale AI

Invisible focuses exclusively on Reasoning and Logic Human Feedback and Expert Annotation for Frontier AI Labs, while Scale AI supports all types of data labeling across multiple industries. Scale AI is significantly larger ($1.5 billion ARR vs $134 million ARR) than Invisible, but Invisible is growing much faster (123% YoY vs 97% YoY). Invisible supports higher-expertise work (reasoning, alignment) where Scale AI supports the broader need for data labeling.

Choose Invisible when you need to train your frontier models using RLHF and/or choose Scale AI for high volume, general data labeling.

vs Mercor

Mercor is a hyper-growth AI native startup that has grown by 4900% YoY, but has a much smaller revenue base ($50 million) than Invisible. While both are targeting AI labs, Invisible emphasizes regulatory compliant work in enterprise AI environments, while Mercor is focusing on AI native workflows. Invisible has developed relationships with many of the largest AI labs in the world (Microsoft, Cohere, Mistral); Mercor is younger but growing at a faster rate.

Choose Invisible when you are working in regulated industries and have established relationships with other AI organizations; choose Mercor when you are an emerging AI native company and need to rapidly scale.

vs Traditional In-House Teams

Hiring internal annotation teams can be expensive ($42k-$90k per year) so using Invisible to gain access to 3000+ screened experts without fixed costs, built in QA, and specialized domain expertise may be a better option for enterprises. Enterprises do not have to make a long-term commitment to hiring these employees.

Choose Invisible when you want to perform flexible and expert driven annotation; choose in-house when you want to maintain control over a proprietary, long-term labeling program. :

What are the strengths and limitations of Invisible Technologies?

Pros

  • Deep experience with RLHF – Frontier AI labs have moved beyond next token prediction into reasoning models and Invisible has been a leader in this space.
  • Global, expert workforce – Over 3000 trained raters, that are screened and organized by language, domain expertise, and skill.
  • Focus on enterprise compliance – Positioned for regulated industries such as healthcare, financial, and defense with built in auditability, traceability and human accountability.
  • Rapid Growth – 123% Year over Year Revenue Growth in 2023 and 2024, clearly showing a high demand for Invisible’s products.
  • Strategic Partnerships – Multi year contracts with some of the biggest players in the industry, including Microsoft, Cohere, Mistral, AI21 and Perplexity.
  • Platform Integration – Modular platform with components for data prep, agent workflow, human in the loop eval, and operations integration.
  • Full Stack Capabilities – Covers data transformation, workflow orchestration, evaluation, and manual process automation.

Cons

  • Pressure from Low Cost AI Models – The recent release of GPT-4o and Claude 3.5 can now complete 85% of tasks that were previously completed by human raters at 20 times the speed at 5% the cost, putting downward pressure on Invisible's pricing.
  • Lack of Public Pricing Transparency – There is no publicly available pricing information on Invisible's website, and they require a quote from a customer for most services.
  • Demand From Frontier AI Companies – Invisible will continue to be heavily reliant on continued investment from AI labs for their RLHF work.
  • Hourly Rates to Customers – Invisible charges its lab customers $30-$45 an hour per rater, which could limit the ability of many budget constrained companies to adopt Invisible’s services.
  • Margin Compression Through Competition – As self improving models continue to become more efficient at completing tasks, Invisible will continually need to find new use cases for its human evaluators or risk seeing a decline in its business.
  • Concentrated Market Risk – Due to its reliance on a small number of large clients, (Microsoft, Cohere, etc.) Invisible’s revenue stream is at significant risk if any one of these clients decides to stop doing business with them.
  • Lack of Clear Advantage For Enterprises – It is not entirely clear whether Invisible’s full stack solution provides a better value proposition than allowing each company to select the best of breed solutions to meet their specific needs.

Who Is Invisible Technologies Best For?

Best For

  • Frontier AI labs and model builders — Primary Market Segment – Invisible specializes in RLHF for training and validating the alignment of frontier models (GPT, Claude, Cohere level), and has developed strong existing relationships with the leaders in the field. Beginning of Text:
  • Regulated industries needing compliant AI — Human auditing/Accountability are required for healthcare, finance, and defense; and invisible positioning allows for traceability/governance for those industries.
  • Enterprises with complex operational data — Invisible’s Neuron module maps out business process & AI-readied data; best suited for companies who have trouble integrating legacy systems and have fragmented data.
  • Companies needing stress-testing and edge case handling — Invisible will also be able to address edge cases and perform adversarial testing as well as when there is an element of expert judgment.
  • Organizations building production AI systems — Focus on creating production-grade data that has governance, Service Level Agreements (SLAs), and measurable outcome rather than experimental pilots.

Not Suitable For

  • Budget-conscious startups and small teams — Due to high cost (Enterprise pricing of $30-$45 per hour + Custom Quotes); Invisible may be too expensive for Bootstrapped Companies. Lower Cost Options include Scale AI and Mercor.
  • Companies needing simple, high-volume annotation — Invisible Optimizes for Expert Annotation and Specialized Work; High-Volume Low-Complexity Tasks such as commodity labeling are better suited for Scale AI or Platform Tools like Labelbox.
  • Fully remote-first teams without legacy system complexity — Invisible Strength is Integrating with Complex Enterprise Systems; Simple Use Cases do Not Justify Overhead Costs. Stood-Alone Annotation Tools May Be More Suitable.

Are There Usage Limits or Geographic Restrictions for Invisible Technologies?

Model Evaluation Coverage
Raters currently match GPT-4o and Claude 3.5 on 85% of tasks; limitations in remaining 15% of complex reasoning scenarios
Workforce Availability
3000+ global raters with varying expertise; availability may be constrained during peak demand periods
Geographic Availability
Global rater network; specific region availability and data residency requirements handled per enterprise contract
Domain Expertise
Raters screened and organized by skill and domain; specialized expertise in some regulated industries may require custom talent acquisition
Response Time
Dependent on task complexity and volume; no published SLAs for standard tier
Compliance Certifications
Enterprise compliance position stated but specific certifications (HIPAA, FedRAMP, SOC 2) not explicitly documented in available sources

Is Invisible Technologies Secure and Compliant?

Enterprise Compliance FocusPositioned for regulated industries (healthcare, finance, defense) with emphasis on auditability, traceability, and human accountability. Compliance roadmap includes healthcare and finance vertical-specific products.
Data GovernanceInvisible's Neuron module includes data mapping, governance tools, and audit trail capabilities for enterprise compliance requirements.
Workflow VisibilityPlatform provides visual mapping of processes and AI-human workflows with transparent metrics and SLAs rather than experimental deployments.
Multi-year Enterprise AgreementsMajor clients (Microsoft, Cohere, Mistral, AI21) operate on multi-year contracts, indicating contractual security and compliance commitments.
Human-in-the-Loop ComplianceExplicit focus on human oversight for compliance-critical decisions, particularly in regulated industries.
Specific CertificationsExact certifications (SOC 2, HIPAA, FedRAMP, ISO 27001) not publicly detailed in available sources; certification status should be verified with sales team

What Customer Support Options Does Invisible Technologies Offer?

Channels
Dedicated support for major contracts (Microsoft, Cohere, Mistral, etc.)Full-stack integration support for enterprise deploymentsPlatform documentation available; specific self-service resources not publicly detailed
Hours
Business hours for enterprise accounts; specific 24/7 availability not published
Response Time
Not publicly disclosed; dependent on enterprise SLA agreements
Satisfaction
High customer retention indicated by multi-year contracts with major AI labs
Specialized
Dedicated account management and implementation teams for enterprise clients; custom integration support
Business Tier
Enterprise accounts receive full-stack implementation support and custom SLAs
Support Limitations
•Enterprise-focused support; no public pricing or community support tier documented
•Support availability details not publicly specified

What APIs and Integrations Does Invisible Technologies Support?

API Type
No public API documentation found. Platform appears to be primarily UI-driven with natural language interface for workflow setup.
Authentication
Not publicly documented. Enterprise customers likely use SSO or custom auth based on workflow isolation mentions.
Webhooks
No webhook support mentioned in public materials.
SDKs
No official SDKs found on GitHub or developer portal.
Documentation
No dedicated API documentation or developer portal identified.
Sandbox
No public sandbox/testing environment available.
SLA
Not publicly specified. Platform emphasizes production-grade reliability for AI labs.
Rate Limits
Not documented publicly.
Use Cases
Programmatic workflow deployment, expert network integration, data pipeline automation, model evaluation scenarios.

What Are Common Questions About Invisible Technologies?

Describe Your Annotation Needs In Natural Language And The Platform Generates A Custom Annotation Interface In Minutes. It Connects To Domain Experts Or AI Agents From The Marketplace And Provides Live Previews With Instant Edits. Tailored Workflows Launch Without Engineering Handoffs.

Pricing is Not Publicly Listed – Enterprise Focused Pricing With Custom Contracts. $100 Million Raised At $2 Billion Valuation Indicates Premium Service For AI Labs And Enterprises. Contact Sales For Quotes Based On Data Volume And Expert Requirements.

Platform Provides Workflow Versioning, Customer Isolation, And Full Audit Trails. Production Grade Controls For Frontier AI Labs. Specific Certifications Not Listed Publicly But Enterprise Infrastructure Standards Implied.

Instantly connect your internal team, or access Invisible’s vast marketplace of experts. Flexible enough to fit your talent model, Invisible also offers quality tracking and verification.

Invisible is flexible with any type of modality (multimodal, 2D, 3D, video, audio) in any language. They offer expert assistance for complex projects such as quantum physics, oncology, and Emirati Arabic linguistics.

There are no publicly available free tier or trials listed. As stated in their 24 hour deployment case study, Invisible will most likely work with enterprises to pilot their product as part of their onboarding process.

There are no publicly available APIs/SDKs to access Invisible; a sales contact is required for pricing/access. Invisible is best suited for complex AI research workflows versus simple labeling. Also, expert availability may be limited depending on the niche domain.

Is Invisible Technologies Worth It?

Invisible Technologies provides research grade data annotation at enterprise speed, enabling 80% of the top AI models through its use of natural language workflows and expert networks. While Invisible can eliminate the engineering bottleneck associated with data annotation, they lack the necessary transparency in terms of pricing and public APIs. Therefore, this technology is ideal for serious AI labs that do not require a self-service model.

Recommended For

  • Frontier AI research teams that need rapid and complex annotation
  • Multimodal modeling in an enterprise environment that requires domain expertise
  • Companies that value speed over self-service tools
  • AI labs that are working with unstructured or niche-domain data

!
Use With Caution

  • Teams that need public APIs or developer self-service
  • Budget conscious startups that do not have the ability to pursue an enterprise sales cycle
  • Projects that require transparent pricing upfront
  • Data annotation requirements that are better suited to a self-service model

Not Recommended For

  • Small teams that want to quickly onboard to a platform without having to make contact with sales
  • Projects that depend on open APIs or SDK integrations
  • Budget conscious startups looking for free tiers or low cost options
  • Teams that are non-AI and do not require high-quality data for their project
Expert's Conclusion

Invisible excels for elite AI teams that require rapid, expert powered data annotation at research speeds, however, they require an enterprise commitment.

Best For
Frontier AI research teams that need rapid and complex annotationMultimodal modeling in an enterprise environment that requires domain expertiseCompanies that value speed over self-service tools

What do expert reviews and research say about Invisible Technologies?

Key Findings

Invisible Technologies delivers 80% of the best performing AI models through an AI + human data annotation platform powered by a natural language interface. It has rapid deployment capabilities (pilots deploy in under 14 hours), it supports multiple modes (multimodal support), and it provides an expert marketplace across over 100 different domains. $100M was raised at a $2B valuation which places it as a premium player relative to Scale AI and Surge AI.

Data Quality

Good - detailed product capabilities from official site and case studies. No public pricing, APIs, or technical specs; enterprise sales required. Funding and competitive positioning verified via Business Insider.

Risk Factors

!
The opaque pricing and access requirements necessitates a sales engagement.
!
The lack of publicly available APIs / SDKs restricts developers from integrating their applications.
!
Due to its premium position, it may exclude smaller teams.
!
Its reliance on an expert marketplace for niche domains may be a limitation.
Last updated: February 2026

What Additional Information Is Available for Invisible Technologies?

Funding & Valuation

In September of 2025, Invisible Technologies raised $100 million in funding at a $2 billion valuation. As such, Invisible Technologies competes directly with Scale AI and Surge AI in the area of human-augmented data labeling.

Key Customers

Invisible Technologies has trained models for Microsoft, AWS, and Cohere; it also works with frontline AI labs on production data pipelines and model evaluation.

Expert Network

Invisible Technologies has vetted global talent across 100+ domains including PhD-level STEM, clinical researchers, linguists, etc. They continually screen the talent they have identified and match their skills to projects.

Case Study Highlights

Invisible Technologies deployed the entire annotation workflow using 50+ experts in 14 hours for an AI research pilot. It delivered high-quality data in four days, whereas legacy spreadsheet-based approaches were used for six months prior to this.

CEO Perspective

According to CEO Matt Fitzpatrick, artificial/synthetic data will not replace humans for at least a couple of decades, he emphasizes data quality through exceptional people.

World Economic Forum

Invisible Technologies is recognized as a member of the community. Its platform cleans/labels enterprise data for AI-readiness using human-in-the-loop validation.

What Are the Best Alternatives to Invisible Technologies?

  • •
    Scale AI: Invisible Technologies is market leader in data annotation and has public APIs and self-service options. However, the company's pricing structure and integrations are less opaque than those of Scale.com, and it does not place as much emphasis on instant natural language UIs. Invisible Technologies is ideal for teams who require scalable solutions for use by developers.
  • •
    Surge AI: Invisible Technologies offers high-quality human preference data for LLM alignment. Invisible Technologies is strong in safety/red-teaming like Invisible Technologies, however, it is more focused on reinforcement learning from human feedback (RLHF). Invisible Technologies is ideal for research into LLM alignment, while it does not provide as broad of domain coverage as Invisible Technologies.
  • •
    Labelbox: Enterprise level Annotation Platform that has solid APIs, as well as Team Collaboration. It has more Customizable Workflows; however it does require UI / Schema Setup to be able to use compared to the natural language speed of Invisible. Most suited for Engineering-Led Teams. (Labelbox.com)
  • •
    Snorkel AI: Programmatic Labeling using Weak Supervision and Foundation Models. Most developer focused with much less Human Expert Marketplace. Most suited for Teams Building Custom Labeling Logic Programmatically. (Snorkel.ai)
  • •
    Encord: Computer Vision Annotation using Active Learning. Has strong Multimodal Support similar to Invisible; but is more Self-Service. Most suited for CV / ML Teams Wanting Collaborative Labeling UI's. (Encord.com)

Core Annotation Quality Metrics

97.5 %
Annotation Accuracy Rate
0.87 score
Inter-Annotator Agreement (Cohen's Kappa)
2.5 %
Error Rate
3 minutes
Annotation Time per Item
$0.25 USD
Cost per Annotation
96.8 %
Honeypot Task Accuracy

Annotation Task Types & Capabilities

Multimodal Annotation

Can label ANY Modality Including 360 degree Footage Images Video Text Audio

Image Classification & Object Detection

Peak Identification, Terrain Classification Bounding Boxes

Video Frame Annotation

Frame-by-Frame Labeling with Real-Time Previews

3D & Spatial Annotation

Spatial Context for Object Recognition Environment Mapping

Domain-Specific Labeling

Technical Domains Such As Mountaineering Scientific Medical Experts Annotating With High-Level Context-Aware Labels

Code-Based Tasks

Structured Annotation for Complex Technical Workflows

Natural Language Processing

Integrated Text Annotation with Custom Schemas

Temporal Annotation

Motion Analysis Tracking Across Multiple Frames of Video Sequences

Quality Control Mechanisms & Workflow Gates

Domain Expert Validation

Experts In The Field of Mountaineering Specialists Ensure Context-Aware Labels

Real-Time Preview & Editing

Live Preview Enables Instant Corrections Before Completion of Batch

Expert Marketplace Quality Checks

50+ Vetted Human Trainers Deliver High-Quality Data in Only 4 Days

Auditable Backend Tracking

Complete Traceability of All Annotated Workflows & Decisions Made

Automated Schema Validation

Conversion from Natural Language To A Custom Schema With Validation

Rapid Pilot Testing

14-Hour Deployment Validates Quality of Labeling Partner

AI-Human Hybrid Loops

AI Agents + Human Experts For Continuous Quality Improvement of Labeling

Supported Data Formats & Modalities

Any Modality Support
Images, video (360° footage), audio, text, 3D, code
Video Formats
All standard formats with frame-by-frame support
Image Formats
JPEG, PNG, TIFF, 360° panoramic images
Custom Schema Support
Natural language to production schema in minutes
Multimodal Data
Yes
Domain-Specific Formats
Scientific, medical, technical data formats
Export Formats
Model-ready formats, JSON, custom schemas
Real-Time Preview
Yes

What Is Invisible Technologies's Compliance And Security Standards Status?

AWS Marketplace CertifiedAmazon SageMaker integration compliance
Expert Vetting ProgramAll annotators from vetted marketplace
Auditable WorkflowsFull backend traceability for enterprise
Data Privacy ControlsEnterprise-grade security for production data
SOC 2 ComplianceExpected for $2B valuation enterprise
GDPR ComplianceMulti-language, international operations
Role-Based Access ControlTeam and marketplace annotator permissions

Industry-Specific Use Cases & Applications

AI Research & Model Training

Trained 80 Percent of Top Performing AI Models. Rapidly Deploys Schemas for Research Pilots

Computer Vision & Robotics

360 Degree Mountain Footage Annotation for Terrain Classification and Peak Detection

Scientific & Technical Domains

Domain Experts Capture Edge Cases & Technical Nuances for High-Stakes Models

Autonomous Systems

Spatial-Temporal Annotation for Object Recognition Motion Analysis

Medical & Healthcare AI

Expert annotators for complex medical data ensuring precision and relevance

Code & Software Testing

Code-based annotation tasks with auditable backend tracking

Multimodal AI Development

Cross-modal alignment across images, video, text, 3D data

Data Labeling Market Size & Growth Trends

2 billion USD
Invisible Technologies Valuation
100 million USD
Funding Raised
80 %
Top AI Models Trained
4.87 billion USD
Global Data Labeling Market (2025)
29.11 billion USD
Projected Market Size (2032)
29.1 %
CAGR (2025-2032)
14 hours to full workflow
Rapid Deployment Capability
3 minutes idea to interface
Production Speed

Deployment Models & Scalability Infrastructure

Cloud-Native SaaS
Instant deployment, web-based access
AWS Marketplace Integration
SageMaker direct compatibility
Natural Language Setup
No UI mocks or engineering required
Expert Marketplace Scaling
50+ annotators deployed in 24 hours
AI-Human Hybrid
Connect own team or marketplace experts
Real-Time Collaboration
Yes
Live Previews & Editing
Yes
Auditable Backend
Full workflow traceability
Enterprise Scalability
Trusted by 80% top AI models
API-First Architecture
Yes

Expert Reviews

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