Duvi vs FigureLabs: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Duvi and FigureLabs — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Duvi

Duvi DigiIQ, Inc.

Freemium

Build voice and chat support agents by describing them in conversation; one configuration answers on your website, WhatsApp and phone line.

Conversational Agent Builder: Creating an agent opens a conversation with a builder that writes the system prompt, picks a model and ingests the websites the agent should answer from, so setup is a dialogue rather than a configuration form.
Unified Omnichannel Configuration: One agent configuration serves website chat, a WhatsApp number and a phone line, with the same knowledge behind every channel so context is not lost when a customer switches.
Live Knowledge Lookups: The agent checks your connected store as it answers, so stock and catalogue responses reflect what is actually available at that moment rather than a stale snapshot.
Website Actions: With the customer's instruction the agent operates the on-page controls you allow, completing the task in front of them instead of handing them a link and instructions.
Grounded Answering: The agent answers from the pages you point it at and says so when the information is not there, rather than guessing.
Preview Before Launch: Agents are tested in Preview and only go live once the domain is allowed and a snippet is pasted on your site.
Broad Connector Library: Sign-in level integrations for Shopify, WooCommerce, Wix, Salesforce Commerce Cloud, Stripe, PayPal, Notion, Airtable, Webflow, Linear, monday.com, Sentry, Supabase, Cloudflare and Zapier.
Team Workspace: Staff query the day's conversations and orders through their own authorized connection, so the answer reflects the order a customer placed moments ago.

Ecommerce Support Deflection: A Shopify store answers stock, shipping and returns questions automatically, with the agent reading live catalogue data instead of a static FAQ.
Lead Capture With Context: An agent takes a caller's email or number and routes it to the team with the whole conversation attached, so nobody asks the customer to repeat themselves.
Phone Line Replacement: A small team replaces a recorded phone menu with an agent that answers real questions using the same knowledge base as the website chat.
WhatsApp Commerce: A brand serving customers primarily on WhatsApp runs the same support agent there without maintaining a separate bot.
Startup Support Coverage: An early-stage team keeps answering customers around the clock while engineers focus on building the product.
Enterprise Support Augmentation: An established support operation adds agents to an existing stack via connectors rather than replacing its tooling.

Freemium

AI agent that creates publication-ready scientific figures via text-to-figure, image-to-figure, and vectorization.

Text-to-Figure Generation: Creates complete, composed scientific figures from plain-text descriptions, allowing users to specify panels, annotations, and figure layout that the agent renders automatically.
Image-to-Figure Conversion: Transforms input images (e.g., plots, microscopy snapshots, schematics) into polished figure components suited for publication, preserving scientific detail while improving presentation.
Vectorization and Editable Output: Converts raster graphics into vector representations so figures are editable and scalable for high-resolution publication needs.
Publication-Ready Styling: Applies formatting and styling conventions appropriate for academic journals, producing high-resolution outputs that reduce manual rework before submission.
Rapid Iteration: Generates and refines figures in seconds, enabling fast prototyping and repeated adjustments during manuscript or presentation development.
Precision Preservation: Focuses on preserving underlying data clarity and scientific details while enhancing visual clarity and label legibility for reproducible visuals.
Text-to-figure generation from natural-language prompts
Image-to-figure conversion (convert raster inputs into cleaned, publication-ready figures)
Vectorization of raster graphics to vector formats (SVG)
Fast generation workflow (seconds-scale) for rapid iteration
Outputs optimized for publication (high-resolution and editable vector formats)

Preparing manuscript figures for journal submission: generate composed, publication-ready multi-panel figures from descriptions and source images to accelerate paper submission.
Converting lab outputs into editable graphics: turn raster plots or microscope images into vectorized, editable figures for revision and scaling without quality loss.
Rapid prototyping of visual results: create multiple figure variants quickly to test layouts, annotations, and styles during manuscript drafting or poster design.
Recreating figures from text or notes: produce visual representations of experimental setups, workflows, or conceptual diagrams from written descriptions for methods or review articles.
Improving figure consistency across a manuscript: standardize styling, labels, and panel layouts across multiple figures to meet journal formatting requirements and improve readability.
Create publication figures for manuscripts, posters, and presentations
Convert hand-drawn or raster diagrams into editable vector figures
Rapidly prototype visualizations from experimental descriptions
Produce consistent, publication-ready figure sets with minimal manual redrawing