Vertesia is a platform that builds intelligent AI agents to automate internal research, workflows, and complex knowledge tasks within organizations. Designed for teams that deal with high volumes of information and decision-making, Vertesia enables users to deploy custom autonomous agents that can think, reason, search, and summarize across internal data sources.
By combining retrieval-augmented generation (RAG), secure document handling, and task orchestration, Vertesia acts like an AI-powered analyst that works around the clock. It eliminates repetitive manual work, accelerates analysis, and ensures that important insights are delivered directly to the people who need them—without compromising on security.
Vertesia is built for enterprises that want to leverage AI while maintaining control over data, compliance, and intellectual property.
Features
Vertesia offers a rich suite of features that make it suitable for both technical and non-technical users within research-intensive organizations:
Autonomous AI Agents: Custom agents that autonomously perform research tasks like summarizing documents, answering questions, and preparing briefings.
Document Understanding: Ingests and understands PDFs, slide decks, spreadsheets, and knowledge bases with high accuracy.
Retrieval-Augmented Generation (RAG): Connects language models with enterprise data to improve relevance and reduce hallucinations.
Task Decomposition: Breaks down complex questions into multiple subtasks that are executed intelligently by agents.
Memory and Context: Agents retain memory over tasks and sessions to provide contextual and consistent outputs.
Natural Language Interface: Interact with agents using simple, conversational prompts with no coding required.
Enterprise-Grade Security: SOC 2-compliant infrastructure and private cloud deployments to ensure data privacy and compliance.
Multi-Source Search: Agents can search across file systems, cloud storage, internal wikis, and databases.
Analytics and Monitoring: Full visibility into how agents operate, what they access, and how decisions are made.
Custom Integration: Integrate with your company’s existing tools, including Slack, Notion, Confluence, and Google Workspace.
How It Works
Vertesia starts by connecting to your organization’s internal data sources—such as shared drives, knowledge bases, and structured databases. Once the data is ingested, Vertesia’s AI agents can be deployed to interact with it on demand or according to pre-set workflows.
When a user gives an instruction like “Summarize all key updates from this quarter’s investor reports,” Vertesia decomposes the task into smaller subtasks. The AI agent then retrieves relevant documents, extracts important data points, analyzes trends, and generates a coherent summary—all autonomously.
Agents can be set up for recurring tasks like weekly reports or configured to support ad-hoc queries. Because the system uses RAG, it references actual content from your documents, reducing hallucination and increasing factual accuracy.
All activity is logged, auditable, and privacy-compliant, giving enterprise teams full control over how AI operates within their workflows.
Use Cases
Vertesia is purpose-built for high-performance teams that rely on research and internal knowledge:
Strategy and Research Teams: Automate competitive analysis, market research, and internal briefings.
Finance and Investor Relations: Prepare earnings summaries, forecast comparisons, and document reviews.
Consulting Firms: Rapidly analyze client materials and deliver insights faster without manual document processing.
Legal and Compliance Teams: Extract and summarize contractual language or regulatory guidelines across complex files.
Knowledge Management: Keep internal knowledge bases up to date by indexing and summarizing new materials.
Operations and Planning: Analyze reports, spreadsheets, and dashboards to support strategic decisions.
Product Teams: Summarize user feedback, research reports, and feature documentation across channels.
Pricing
As of the latest information available on the official website, Vertesia does not publish fixed pricing. The platform is currently focused on enterprise use and offers custom deployments tailored to each organization’s infrastructure, data needs, and use cases.
Prospective customers can request a demo or schedule a call with the Vertesia team to receive a personalized proposal based on the number of users, data volume, and level of customization required.
Strengths
Vertesia offers a strong combination of AI intelligence, data security, and enterprise readiness:
Built for Enterprises: Designed to meet the privacy, compliance, and scalability needs of large organizations.
High Accuracy and Contextuality: Uses RAG and task decomposition to deliver fact-based outputs.
Fully Autonomous Agents: Operates without constant human oversight, reducing time spent on repetitive knowledge work.
Multi-Format Intelligence: Understands documents in PDF, Excel, and PowerPoint formats.
Modular and Customizable: Can be adapted to different departmental needs without rebuilding from scratch.
Human-Grade Output: Summaries and reports match the quality of professional analysts and researchers.
Transparent and Auditable: Logs every step the AI takes, building trust and accountability.
Drawbacks
While Vertesia is a powerful platform, it may not suit every organization:
Enterprise Focus: Currently optimized for larger teams and enterprises, not for individual users or startups.
No Public Pricing: Lack of transparent pricing may delay decision-making for procurement teams.
Requires Data Access Setup: Organizations need to invest time in configuring secure access to their internal sources.
Not for Creative Use Cases: The platform focuses on analytical and structured research tasks, not creative content generation.
Comparison with Other Tools
Vertesia vs. Glean: Glean is focused on AI-powered enterprise search. Vertesia goes beyond search to perform multi-step reasoning, analysis, and reporting using autonomous agents.
Vertesia vs. Harvey: Harvey is built for legal workflows and contract analysis. Vertesia is broader, supporting multiple departments and use cases across industries.
Vertesia vs. ChatGPT Enterprise: ChatGPT provides general AI capabilities. Vertesia adds task decomposition, document analysis, and end-to-end task automation specific to enterprise knowledge work.
Vertesia vs. Zapier or Make: While Zapier automates workflows through triggers and actions, Vertesia applies intelligence to decision-making and knowledge synthesis, making it better suited for research and analysis.
Customer Reviews and Testimonials
While Vertesia is in a controlled rollout phase, early adopters have praised its impact on productivity and decision support.
A strategy executive at a global consulting firm noted:
“Vertesia is like having a team of analysts that never sleeps. We use it daily to prepare briefs, compare market data, and distill hundreds of documents into one actionable report.”
A product operations lead shared:
“The AI agents understand the nuance in our data and pull insights that would take our team hours to compile. It’s changed how we prepare for launches and reviews.”
The platform is frequently highlighted for its blend of deep AI reasoning and enterprise-grade execution.
Conclusion
Vertesia is redefining how organizations interact with their internal knowledge. By enabling autonomous AI agents to handle research, analysis, and synthesis tasks, it frees up teams to focus on strategy and decision-making. With a strong emphasis on security, accuracy, and usability, Vertesia is positioned as a top-tier solution for enterprises that want to unlock the value in their documents and data.
Whether you’re managing investor relations, consulting with clients, or running operations across complex systems, Vertesia helps you access the insights you need faster—and with less manual effort. For any organization serious about scaling internal intelligence securely, Vertesia is a forward-thinking investment.
