Introducing AI Slides

Generate PPT Files That Don’t Feel Like AI Slop

A new framework for building AI agents.

Compare

V7 vs. Hyperscience

V7 vs. Hyperscience

V7 vs. Hyperscience

Searching for a good Hyperscience alternative?

Searching for a good Hyperscience alternative?

Searching for a good Hyperscience alternative?

Evaluating Hyperscience as an intelligent document processing platform

Evaluating Hyperscience as an intelligent document processing platform

V7

vs.

(h[s]) logo

Get started

Why choose V7 over Hyperscience?

Both platforms automate document-intensive workflows. V7 Go adds specialized AI agents and visual grounding, while Hyperscience focuses on IDP extraction.

Overview

Visual Source Verification

V7 Go provides AI citations that visually link every extracted data point to its exact location in source documents, enabling interactive verification and compliance audit trails.

Pre-Built Specialized Agents

V7 Go offers 300+ pre-built AI agents designed for specific roles across finance, legal, insurance, and real estate, enabling faster deployment than building extraction workflows from scratch.

Rapid Implementation

V7 Go delivers measurable outcomes within 11 days through white-glove service with solution engineers, compared to longer enterprise implementation cycles typical of traditional IDP solutions.

Features

What makes V7 Go the best Hyperscience alternative

Compare document automation capabilities and enterprise features

Features

Get started

V7

(h[s]) logo

Hyperscience

vs.

Visual source grounding

Visual source grounding

AI citations link every output to exact source locations with interactive highlighting for verification

AI citations link every output to exact source locations with interactive highlighting for verification

V7

AI citations link every output to exact source locations with interactive highlighting for verification

QA processes and audit trails focused on extraction validation rather than interactive source linking

QA processes and audit trails focused on extraction validation rather than interactive source linking

Hyperscience

QA processes and audit trails focused on extraction validation rather than interactive source linking

Document extraction accuracy

95-99% accuracy on document processing benchmarks with visual verification capabilities

95-99% accuracy on document processing benchmarks with visual verification capabilities

V7

95-99% accuracy on document processing benchmarks with visual verification capabilities

Up to 99.5% accuracy with proprietary ML models optimized for structured and unstructured documents

Up to 99.5% accuracy with proprietary ML models optimized for structured and unstructured documents

Hyperscience

Up to 99.5% accuracy with proprietary ML models optimized for structured and unstructured documents

Pre-built industry agents

300+ specialized agents for finance, legal, insurance, and real estate ready to deploy

300+ specialized agents for finance, legal, insurance, and real estate ready to deploy

V7

300+ specialized agents for finance, legal, insurance, and real estate ready to deploy

Focuses on document classification and extraction workflows rather than role-specific agents

Focuses on document classification and extraction workflows rather than role-specific agents

Hyperscience

Focuses on document classification and extraction workflows rather than role-specific agents

Low-code workflow builder

Visual workflow designer with conditional logic and human review stages for business users

Visual workflow designer with conditional logic and human review stages for business users

V7

Visual workflow designer with conditional logic and human review stages for business users

Workflow automation capabilities available but primarily focused on document-centric processes

Workflow automation capabilities available but primarily focused on document-centric processes

Hyperscience

Workflow automation capabilities available but primarily focused on document-centric processes

Enterprise compliance

Built for SOX, HIPAA, FDA, KYC/AML compliance with full audit trails and on-premise options

Built for SOX, HIPAA, FDA, KYC/AML compliance with full audit trails and on-premise options

V7

Built for SOX, HIPAA, FDA, KYC/AML compliance with full audit trails and on-premise options

FedRAMP High authorized with HIPAA compliance and enterprise security features

FedRAMP High authorized with HIPAA compliance and enterprise security features

Hyperscience

FedRAMP High authorized with HIPAA compliance and enterprise security features

Human-in-the-loop review

Configurable review stages with feedback loops for continuous improvement

Configurable review stages with feedback loops for continuous improvement

V7

Configurable review stages with feedback loops for continuous improvement

Consensus-based validation methods for extraction accuracy with QA workflows

Consensus-based validation methods for extraction accuracy with QA workflows

Hyperscience

Consensus-based validation methods for extraction accuracy with QA workflows

Pricing

Get started

Hyperscience pricing explained

Both platforms offer custom enterprise pricing based on usage and requirements

Features

Get started

V7

V7 Go pricing is structured around a base platform fee that includes access to the V7 platform with AI agents, plus user licenses and data processing charges based on actual usage and use case requirements. The platform offers transparent pricing that scales predictably with document volume, and premium white-glove service includes building custom integrations with legacy systems, designing industry-specific AI agents by expert solution engineers, and providing hands-on implementation support.

V7 Go pricing is structured around a base platform fee that includes access to the V7 platform with AI agents, plus user licenses and data processing charges based on actual usage and use case requirements. The platform offers transparent pricing that scales predictably with document volume, and premium white-glove service includes building custom integrations with legacy systems, designing industry-specific AI agents by expert solution engineers, and providing hands-on implementation support.

Base platform fee plus user licenses and usage-based data processing charges

White-glove service includes custom integrations and specialized agent development

Free proof of concept with sample documents before commitment

(h[s]) logo

Hyperscience

Hyperscience uses custom enterprise pricing without published rates or self-service tiers. Pricing is typically based on document volume, integration scope, and security requirements. As an enterprise-focused solution serving major organizations like American Express and government agencies, Hyperscience follows traditional enterprise sales cycles with custom quotes. The platform is available through direct enterprise sales with implementation timelines that vary based on deployment complexity and integration requirements.

Hyperscience uses custom enterprise pricing without published rates or self-service tiers. Pricing is typically based on document volume, integration scope, and security requirements. As an enterprise-focused solution serving major organizations like American Express and government agencies, Hyperscience follows traditional enterprise sales cycles with custom quotes. The platform is available through direct enterprise sales with implementation timelines that vary based on deployment complexity and integration requirements.

Custom enterprise pricing with no published rates or self-service options

Pricing based on document volume, integration scope, and security requirements

Traditional enterprise sales cycles with custom implementation timelines

Comparison

Get started

Comparing V7 Go and Hyperscience capabilities

Understanding enterprise pricing and implementation approaches

Features

Get started

V7

Enterprise AI automation platform with specialized agents and visual grounding

V7 Go is an enterprise AI automation platform that extends beyond document extraction to deliver end-to-end workflow automation through specialized AI agents. The platform provides over 300 pre-built agents for finance, legal, insurance, and real estate, with visual grounding that traces every AI output to its exact source location in documents. V7 Go achieves 95-99% accuracy on document processing benchmarks and supports 1M+ token context windows for large document bundles. The platform includes a low-code visual workflow designer accessible to business users, plus white-glove service with solution engineers who build custom integrations and industry-specific agents.

(h[s]) logo

Hyperscience

Enterprise intelligent document processing with ML-driven extraction

Hyperscience is an enterprise AI platform recognized as a Leader by six tier-one analyst firms including Gartner, Forrester, and IDC for intelligent document processing. The platform uses proprietary machine learning models to achieve up to 99.5% accuracy on data extraction from structured and unstructured documents, including handwriting and complex forms. Hyperscience serves major enterprises like American Express, Charles Schwab, and MetLife, as well as government agencies including the US Social Security Administration. The platform is FedRAMP High authorized and offers agentic document automation capabilities that streamline multi-step workflows across enterprise systems.

Testimonials

Get started

Trusted by teams shipping AI to production

What customers say after choosing V7 Go

Features

Get started

Learn more

Get started

Everything you need to run AI in production

A complete platform for document intelligence and workflows

Features

Get started

Your Entire Tech Stack, Perfectly Connected

1,000+ Integrations Across Your Entire Stack

Connect every tool your teams rely on — from CRM to finance to devops — all in a single platform.

The Foundation

Security You Can Trust, Compliance You Can Prove

ISO, HIPAA, SOC 2, GDPR and more — your data stays protected under world-class security and governance.

Unity Across Emails, Files, Documents & Data

Works With Everything You Already Use

Data

Calls

Files

Deals

Emails

People

Paper Docs

Customers

Documents

Conversations

Calls

Data

Deals

Files

People

Emails

Customers

Paper Docs

Conversations

Documents

Data

Calls

Files

Deals

Emails

People

Paper Docs

Customers

Documents

Conversations

Calls

Data

Deals

Files

People

Emails

V7 ingests emails, meetings, PDFs, paper scans, conversations, data sources, customer records, contracts — and makes them instantly usable.

Multi-Model Power, Zero Lock-In

Integrations That Actually Integrate

Connect every tool your teams rely on — from CRM and finance to DevOps and data systems — all flowing through a single platform.

A New Class of AI Agents

300+ Expert-Built Agents for Real Work

Designed by industry leaders and deeply connected to your business — V7 Agents execute workflows with contextual, up-to-date intelligence.

Features

Get started

From First Call to Commercials in 11 Days

A Fast, Proven Path to Value

Day 1

Introductory Call

Day 2

POC Scoping

Day 3

POC Kickoff

Day 5

POC Check-in

Day 10

POC Results Review

Day 11

Commercial discussions

Intro call, POC scoping, kickoff, check-ins, results review and commercial discussion — V7 moves from first contact to measurable outcomes in just 11 days.

Configure Anything to Fit Your Workflow

Built to Adapt. Designed Without Limits.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Min

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Customize every workflow, rule, interface and reasoning step. Adjust prompts, models, inputs, outputs, citations and integrations — full flexibility with zero constraints.

Index Knowledge

All Knowledge in One Place

Investment memo generation

AI contract review

Property valuation AI

Claims processing automation

Financial statement analysis

Real estate lease abstraction

Portfolio management automation

Offering memorandum analysis

Insurance claims automation

OCR + data extraction

Due diligence automation

Pitch deck analysis

Document processing AI

Investment banking analysis

Insurance underwriting automation

Data room analysis

10-Q report analysis

Financial statement analysis

Investment memo generation

AI contract review

Property valuation AI

Claims processing automation

Financial statement analysis

Real estate lease abstraction

Portfolio management automation

Offering memorandum analysis

Insurance claims automation

OCR + data extraction

Due diligence automation

Pitch deck analysis

Document processing AI

Investment banking analysis

Insurance underwriting automation

Data room analysis

10-Q report analysis

Financial statement analysis

Product specs, sales playbooks, compliance policies, brand guides, policies, scripts, competitor briefs — neatly organized in searchable, permissioned Knowledge Hubs.

Performance That Leaves Everything Else Behind

Outperforms LLMs, RPAs, IDPs & Hyperscalers

Hyperscaler

70-80%

LLM's

80-95%

RPA & IDP

80-99%

V7 Go

95-99%

On one-shot benchmarks, V7 Go reaches 95–99% accuracy, surpassing leading LLMs, RPA/IDP tools and hyperscalers across real enterprise workloads.

Your Company’s Brain, Finally Organized

All Knowledge in One Place

Index Knowledge

Product specs, sales playbooks, compliance policies, brand guides, policies, scripts, competitor briefs — neatly organized in searchable, permissioned Knowledge Hubs.

The V7 Product Suite

One Unified Workspace. Endless AI Capabilities.

AI Tables, AI Docs, automated document generation, Knowledge Hubs and powerful integrations — all working together like an AI-native Microsoft Office.

Have questions?

Find answers.

Any more questions?

Contact us

How does V7 Go's visual grounding compare to Hyperscience's audit trail capabilities?

Both platforms provide audit trail capabilities for compliance, but they approach source verification differently. V7 Go's visual grounding creates interactive AI citations that link every extracted data point to its exact location in the source document, allowing users to click on any output and see the highlighted source text or region. Hyperscience provides QA processes and audit trails focused on validating extraction accuracy using consensus methods. For organizations that need to quickly verify AI outputs during human review or demonstrate data provenance to auditors, V7 Go's interactive approach may offer advantages, while Hyperscience's validation methods are well-suited for high-volume extraction workflows.

What are the key differences in document processing accuracy between the platforms?

Hyperscience reports up to 99.5% accuracy on document extraction using proprietary ML models optimized over years of enterprise deployments, with particular strength in handwriting recognition and complex forms. V7 Go achieves 95-99% accuracy on document processing benchmarks while adding visual source verification that allows users to validate outputs against source documents. Both platforms support human-in-the-loop review for quality assurance. The choice may depend on whether your priority is maximum extraction accuracy for high-volume processing or the ability to visually verify and trace outputs for compliance purposes.

How do the platforms differ in their approach to workflow automation?

Hyperscience focuses primarily on document-centric automation with agentic capabilities for multi-step document workflows, classification, extraction, and validation. V7 Go takes a broader approach with specialized AI agents designed for specific roles and industries, combined with a low-code visual workflow designer that enables business users to build complete automation pipelines with conditional logic and human review stages. V7 Go's approach extends beyond extraction to include analysis, reasoning, and integration with external systems, while Hyperscience excels at high-accuracy document processing within its IDP focus.

Which platform is better suited for specific industries like finance or insurance?

Both platforms serve regulated industries effectively. Hyperscience has proven deployments at major financial institutions like American Express and Charles Schwab, as well as insurance companies like MetLife, with FedRAMP High authorization for government use. V7 Go offers 300+ pre-built specialized agents across finance, legal, insurance, and real estate, with agents designed for specific roles like financial planning analysts, legal bill auditors, and claims processors. Organizations may prefer Hyperscience for high-volume extraction workflows or V7 Go for role-specific automation with visual grounding.

How do implementation timelines and support models compare?

V7 Go emphasizes rapid implementation with white-glove service, offering proof of concept within days and measurable outcomes within 11 days of first contact. Solution engineers build custom integrations and design industry-specific AI agents as part of the service. Hyperscience follows traditional enterprise sales cycles with implementation timelines that vary based on deployment complexity, integration requirements, and security needs. Both platforms offer enterprise support, but V7 Go's approach may suit organizations seeking faster time-to-value, while Hyperscience's model is established for large-scale enterprise deployments.

Have questions?

Find answers.

Any more questions?

Contact us

How does V7 Go's visual grounding compare to Hyperscience's audit trail capabilities?

Both platforms provide audit trail capabilities for compliance, but they approach source verification differently. V7 Go's visual grounding creates interactive AI citations that link every extracted data point to its exact location in the source document, allowing users to click on any output and see the highlighted source text or region. Hyperscience provides QA processes and audit trails focused on validating extraction accuracy using consensus methods. For organizations that need to quickly verify AI outputs during human review or demonstrate data provenance to auditors, V7 Go's interactive approach may offer advantages, while Hyperscience's validation methods are well-suited for high-volume extraction workflows.

What are the key differences in document processing accuracy between the platforms?

Hyperscience reports up to 99.5% accuracy on document extraction using proprietary ML models optimized over years of enterprise deployments, with particular strength in handwriting recognition and complex forms. V7 Go achieves 95-99% accuracy on document processing benchmarks while adding visual source verification that allows users to validate outputs against source documents. Both platforms support human-in-the-loop review for quality assurance. The choice may depend on whether your priority is maximum extraction accuracy for high-volume processing or the ability to visually verify and trace outputs for compliance purposes.

How do the platforms differ in their approach to workflow automation?

Hyperscience focuses primarily on document-centric automation with agentic capabilities for multi-step document workflows, classification, extraction, and validation. V7 Go takes a broader approach with specialized AI agents designed for specific roles and industries, combined with a low-code visual workflow designer that enables business users to build complete automation pipelines with conditional logic and human review stages. V7 Go's approach extends beyond extraction to include analysis, reasoning, and integration with external systems, while Hyperscience excels at high-accuracy document processing within its IDP focus.

Which platform is better suited for specific industries like finance or insurance?

Both platforms serve regulated industries effectively. Hyperscience has proven deployments at major financial institutions like American Express and Charles Schwab, as well as insurance companies like MetLife, with FedRAMP High authorization for government use. V7 Go offers 300+ pre-built specialized agents across finance, legal, insurance, and real estate, with agents designed for specific roles like financial planning analysts, legal bill auditors, and claims processors. Organizations may prefer Hyperscience for high-volume extraction workflows or V7 Go for role-specific automation with visual grounding.

How do implementation timelines and support models compare?

V7 Go emphasizes rapid implementation with white-glove service, offering proof of concept within days and measurable outcomes within 11 days of first contact. Solution engineers build custom integrations and design industry-specific AI agents as part of the service. Hyperscience follows traditional enterprise sales cycles with implementation timelines that vary based on deployment complexity, integration requirements, and security needs. Both platforms offer enterprise support, but V7 Go's approach may suit organizations seeking faster time-to-value, while Hyperscience's model is established for large-scale enterprise deployments.

Have questions?

Find answers.

How does V7 Go's visual grounding compare to Hyperscience's audit trail capabilities?

Both platforms provide audit trail capabilities for compliance, but they approach source verification differently. V7 Go's visual grounding creates interactive AI citations that link every extracted data point to its exact location in the source document, allowing users to click on any output and see the highlighted source text or region. Hyperscience provides QA processes and audit trails focused on validating extraction accuracy using consensus methods. For organizations that need to quickly verify AI outputs during human review or demonstrate data provenance to auditors, V7 Go's interactive approach may offer advantages, while Hyperscience's validation methods are well-suited for high-volume extraction workflows.

What are the key differences in document processing accuracy between the platforms?

Hyperscience reports up to 99.5% accuracy on document extraction using proprietary ML models optimized over years of enterprise deployments, with particular strength in handwriting recognition and complex forms. V7 Go achieves 95-99% accuracy on document processing benchmarks while adding visual source verification that allows users to validate outputs against source documents. Both platforms support human-in-the-loop review for quality assurance. The choice may depend on whether your priority is maximum extraction accuracy for high-volume processing or the ability to visually verify and trace outputs for compliance purposes.

How do the platforms differ in their approach to workflow automation?

Hyperscience focuses primarily on document-centric automation with agentic capabilities for multi-step document workflows, classification, extraction, and validation. V7 Go takes a broader approach with specialized AI agents designed for specific roles and industries, combined with a low-code visual workflow designer that enables business users to build complete automation pipelines with conditional logic and human review stages. V7 Go's approach extends beyond extraction to include analysis, reasoning, and integration with external systems, while Hyperscience excels at high-accuracy document processing within its IDP focus.

Which platform is better suited for specific industries like finance or insurance?

Both platforms serve regulated industries effectively. Hyperscience has proven deployments at major financial institutions like American Express and Charles Schwab, as well as insurance companies like MetLife, with FedRAMP High authorization for government use. V7 Go offers 300+ pre-built specialized agents across finance, legal, insurance, and real estate, with agents designed for specific roles like financial planning analysts, legal bill auditors, and claims processors. Organizations may prefer Hyperscience for high-volume extraction workflows or V7 Go for role-specific automation with visual grounding.

How do implementation timelines and support models compare?

V7 Go emphasizes rapid implementation with white-glove service, offering proof of concept within days and measurable outcomes within 11 days of first contact. Solution engineers build custom integrations and design industry-specific AI agents as part of the service. Hyperscience follows traditional enterprise sales cycles with implementation timelines that vary based on deployment complexity, integration requirements, and security needs. Both platforms offer enterprise support, but V7 Go's approach may suit organizations seeking faster time-to-value, while Hyperscience's model is established for large-scale enterprise deployments.

Precision AI for Institutional Workflows

Build once.

Deploy across the team.

Improve over time.

Request a demo

30 minutes

About

Build once.

Deploy across the team.

Improve over time.

Request a demo

30 minutes

About

Build once.

Deploy across the team.

Improve over time.

Request a demo

30 minutes