Corvic AI
by Corvic AI
Agentic data engine that turns PDFs, images, sensor logs and tables into cited answers and pipelines
Corvic AI is an agentic data platform for enterprise operations teams in manufacturing, life sciences and finance. It converts mixed data such as PDFs, images, sensor logs and tables into structured outputs and cited answers, cutting the manual engineering those teams would otherwise do first.
Corvic AI builds what it calls an Intelligence Composition Platform: users ask questions in plain English about their documents, tables and tools, and get back answers, apps or data pipelines. Founders Farshid Sabet (CEO), Donald Nguyen and Gurbinder Gill all worked at Katana Graph, and the company left stealth in April 2025 with a $12M seed led by M Ventures and Bosch Ventures. SiliconANGLE described its two original components at that time: Mixture of Spaces, which organizes text, tabular, image and time-series data into separate spaces with their own processing tools, and Adaptive Chain of Actions, an orchestration engine that builds a reasoning workflow per query. Corvic V3 reached general availability on May 12, 2026, alongside Individual Plans starting at $20 a month and listings on AWS Marketplace and Google Cloud Marketplace, plus availability in Microsoft Azure. The current product includes an agent harness, scheduled playbooks, web apps, data pipelines and an agent marketplace. Answers carry inline citations, and Corvic says a second model fact-checks numbers, dates and citations. The site lists 56 integrations, including Snowflake, Databricks, BigQuery and Salesforce, plus an MCP endpoint. Corvic Desktop runs on a Mac locally, in the cloud or both, and private VPC deployment is reserved for Enterprise. Pioneer customers named in the release are Bosch, Merck and Creative Labs, using it for knowledge graphs from engineering schematics, FDA submission preparation, invoice processing and field service root cause analysis. Its token savings and memory claims are vendor statements without published benchmarks.
A head of data or AI at a manufacturer, life sciences company or financial operations group with valuable knowledge locked in schematics, PDFs, sensor logs and tables.
Multimodal data becomes structured outputs and cited answers without first building a separate stack of vector, graph and retrieval tools.
At a Glance
- Category
- Data & Analytics
- Pricing
- Subscription, Usage-based, Contact for pricing
- Target Market
- Data Scientists, AI Engineers, Enterprise Operations Teams, CTOs
- Deployment
- Cloud-first, Hybrid, Multi-cloud
Key Features
- ✓Multimodal data engine
Converts images, PDFs, sensor logs and tables into structured outputs, so production applications can use data that normally needs manual preparation.
- ✓Cited answers with a second-model check
Attaches inline citations to source data, and Corvic says a second model fact-checks numbers, dates and citations in each output.
- ✓Scheduled playbooks
Runs saved workflows and re-syncs connected sources daily, weekly or monthly, which keeps recurring analyses current without someone restarting them.
- ✓Connectors and MCP endpoint
Lists 56 integrations including Snowflake, Databricks, BigQuery and Salesforce, and exposes an MCP endpoint with scoped API tokens for agent access.
- ✓Corvic Desktop
Runs on a Mac laptop locally, in the cloud or both, which lets an individual work with sensitive files on their own machine.
- ✓Private VPC deployment
Enterprise customers can deploy inside a private VPC with SSO, encryption and zero data retention, keeping customer data in their control.
Capabilities
Use Cases
- •Engineering knowledge graphs
A manufacturer builds knowledge graphs from engineering schematics, making design information searchable instead of locked inside drawings and scattered documents.
- •Regulatory submissions
A life sciences team prepares FDA-ready submission material from mixed documents, reducing the manual assembly work before regulatory review.
- •Semiconductor root cause analysis
Corvic's Semiconductor Expertise Assistant automates root cause analysis in chip design, a process PYMNTS reports took experts about two weeks per analysis.
- •Invoice processing for ERP
A finance operations team extracts structured invoice data and passes it to ERP systems, cutting manual entry from the process.
Ideal For
Best For
- ✓Manufacturers building knowledge graphs from engineering schematics and technical documents
- ✓Life sciences teams preparing documentation for FDA submissions from mixed source material
- ✓Field service and semiconductor teams automating root cause analysis across logs and reports
- ✓Finance operations teams extracting invoice data into ERP systems
- ✓Individual AI engineers and analysts who want to try the platform without enterprise procurement
Not Ideal For
- ✗Buyers who need independent reviews before shortlisting, because we found no G2 rating and only negligible Hacker News discussion
- ✗Small teams that need SSO, compliance controls or private deployment, since those are reserved for the custom-priced Enterprise plan
- ✗Teams with clean, purely tabular data already served by a warehouse and BI tool, who would not use the multimodal processing they would be paying for
Deployment
Market Analysis
Pros
- ✓Published entry pricing from $20 a month with a 7-day trial, so a team can test it before talking to sales
- ✓Answers link to source data with inline citations, which makes outputs checkable by a reviewer
- ✓Named industrial and pharma adopters, including Bosch and Merck, both of which also have venture arms invested in the company
Cons
- ✗No G2 rating found and Hacker News stories score about one point each, so independent evidence of production use is thin
- ✗Claims of 10x token savings and unlimited context memory are vendor statements with no published benchmark we could find
- ✗SSO, compliance and private deployment are gated to custom-priced Enterprise, and the Desktop product is described as running on a Mac
- ✗Bosch and Merck are both customers and investors through their venture arms, so those references are not arm's-length endorsements
Pricing
Developer
$20/mo
- ✓1 developer seat
- ✓10M AI tokens
- ✓1,000 web search queries
- ✓7-day free trial
Premium
$200/mo
- ✓10 developer seats
- ✓50M AI tokens
- ✓5,000 web search queries
- ✓7-day free trial
Enterprise
Contact for pricing
- ✓SSO
- ✓Compliance
- ✓Private deployment
- ✓Custom support and limits
Plans are metered on seats, AI tokens and web searches, and overages bill automatically at $20 per extra seat, $5 per million tokens and $20 per 1,000 searches. SSO, compliance and private deployment are Enterprise only, at custom pricing. The homepage also advertises a free account with no credit card, while the pricing page shows a 7-day trial, so confirm the terms.
Security & Compliance
Sources
This page was written from 6 sources, 4 on domains other than corvic.ai.
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