Can general AI solve this?

Maybe you can turn to ChatGPT or Claude to upload your varying datasets and get a perspective with all of your data points in mind, but token limits and an inability to process obscure file formats have you hitting a wall here too as your CEO demands a response.

Does an answer engine exist that can crawl all of your data and give fast, accurate answers in a multimodal capacity?

Yes, fortunately Lium was built with advanced industries in mind. You can upload any file type, no matter how complex, into your AI environment and get technically accurate, multimodal responses to your most challenging questions.

Follow along to learn more about what multimodal AI is, and how it is solving big problems in complex sectors.

Multimodal artificial intelligence (AI) platforms are AI systems that are able to blend multiple data types to provide answers and generate outputs that lie at the intersection of those modalities. A basic example would be making a request in text and receiving a picture as an output. A more advanced example would be blending a 3D seismic cube with well logs and generating a text output that uncovers the key information a user is looking for with their query.

Multimodality allows advanced, data-dense industries to save time on extracting insights from their diverse proprietary data . Once datasets are uploaded to Lium, your work environment will provide industry-specific answers to complex problems with precise accuracy.

Traditional vs. Multimodal AI

As explained by IBM’s Carnegie Mellon framework, data types are fundamentally different in quality and structure (heterogeneity), they share complementary information across modalities (connections), and the value comes from how they interact when brought together (interactions).

General AI platforms cannot process and blend this heterogenous data from complementary modalities because platforms like ChatGPT & Claude:

• typically are limited to one single output at a time (a single modality)
• can’t accept obscure file types
• are only able to accept files up to a certain size regardless of file type

Industries like energy and aerospace collect and analyze millions of data points in various (often obscure) formats and metrics. Lium’s multimodal AI platform can process these datasets regardless of their size and format.

Once your various datasets are processed by Lium, your answer engine responses will overlay the datasets to give you accurate answers fast by using a complementary data point as an anchor across all files.

Multimodal AI is often described as a machine learning architecture: different types of data get encoded into shared mathematical representations, and the model learns to reason across them by pulling the representations together. Consumer models like Gemini, Claude and GPT-5.5 have built in this capability for the most common data types like text, images and audio, but have no capacity to work with the vast majority of complex data types.

Lium works differently. And when you work in an advanced industry that requires nuanced, data-backed answers to complex questions, the distinction matters.

How Lium’s Multimodality Works

Unlike multimodal models that encode different data types, Lium keeps data in its native formats, and leverages an anchor-based approach to understand how different modalities interact.

Here are the ways that Lium’s multimodal AI solution for advanced industries stands out from generic AI products:

Data Stays in Its Native Format

Working with obscure file types? No worries. For specialized formats commonly used in advanced industries, Lium writes the code for you to convert the data into a machine readable format that can be aligned across modalities.

When files are shared with Lium, the data is indexed and integrated into your entire data environment so that insights can be found across modalities.

Reasoning Anchored to a Point of Interest

Lium integrates datasets around a shared anchor to answer user questions; think geographic locations, a specific asset, a time window, etc.

When any of your team members ask a question, be it an analyst with a complex need or an executive with a high-level question, Lium returns the relevant value from every connected dataset anchored to that same point.

Data anchor example:

Suppose an analyst is evaluating a road intersection. Lium surfaces the temperature (100 degrees Fahrenheit), the precipitation record (1 inch of rain), and the LiDAR terrain classification (flat) of that specific location (the anchor) to answer the analyst's hyper-specific questions.

Three datasets, three scalar outputs, one anchor. No approximation. Just aligned values integrated from each source and presented together.

The Output is Your Data, Not a Model's Interpretation of It

A wrong answer from an engineer or geoscientist can be catastrophic; if they’re going to use AI, its answer needs to be 100% correct.

Other AI platforms require a data engineer to manipulate the data manually prior to use, significantly delaying the time to insight and introducing the risk of inconsistent conversion that can turn a precise measurement into an “educated” guess. Lium captures your domain knowledge, builds it into deterministic workflows to blend your data, so that responses are reliable and repeatable based on what your data actually says.

If you want your artificial intelligence to blend various datasets for a deeper, nuanced understanding of your niche industry and problems, the critical first step is integrating a platform into your tech stack that can process all of your relevant file formats.

General AI often can’t crawl and absorb lesser known file types that are common in advanced industries. And file size limitations hold back tools like ChatGPT or Claude from even crawling a large spreadsheet or PDF file once a certain number of tokens are used.

Lium’s multimodality overcomes these hurdles by converting complex and/or large files into materialized views that extract the key information necessary for analysis and are indexed across your data universe.

Integrate the following file types & beyond into your Lium environment for blended insights across all of your data:

• Text & Documents: reports, contracts, technical papers, field notes, regulatory filings, etc.
• Structured Data: databases, spreadsheets, time series records, sensor telemetry
• Imagery: crawl satellite data, medical scans, industrial inspection photos, remote sensing outputs, etc.
• Audio & Video: environmental sensors, acoustic monitoring, operational footage
• Domain-specific Formats: SEG-Y seismic files, BIM models, FASTQ genomics sequences, GIS raster and vector formats, etc.; ANY of the obscure or legacy file types that advanced industries depend on.

Unlike platforms like ChatGPT that can only accept files up to 512 MB, Lium is an agentic harness that can process and integrate large file sizes at any scale for multimodal reasoning.

You’re tired of sifting through complex datasets for weeks or months on end. And fear the consequences of giving leadership a wrong answer to critical questions. Multimodal AI makes it possible to process complex data and use it to extract accurate insights, fast.

Here are key ways that advanced industries can revolutionize their analysis with multimodality:

Faster Data Integration & Cross-Model Overlay:

No more manually cross-referencing data in various file formats that measure data differently. All of your required datasets are ingested in their original format and accessible from the Lium answer engine almost instantly.

Once your data is processed, the AI cross-references it all simultaneously in a single query using one anchor across all datasets.

Broader, Domain-Specific Context:

Generic AI’s “jack of all trades” approach to reasoning doesn’t work when you’re working in a complex advanced industry; your work requires a deeper understanding of dense data.

Lium was built with advanced industries in mind; integrating your data ensures a nuanced, multimodal understanding of your data repository to answer difficult questions.

Accessible Answers Across Organizations

Analysts with complicated questions aren’t the only ones using Lium. Organizational leaders can query across modalities and get accurate answers without a deep understanding of the underlying data.

High-level questions still return accurate, data-backed responses.

The only thing most advanced industries have in common is the data-dense reasoning they require for decision-making. The types of decisions and data they need to analyze couldn’t be more different.

Here are distinct ways that different organizations are utilizing Lium’s multimodality to extract and interpret data:

• Geospatial & Remote Sensing: reasoning across satellite imagery, LiDAR point clouds, vector datasets, and field reports simultaneously
• Subsurface Exploration: synthesizing seismic volumes, well logs, core sample imagery, and formation documentation in a single analysis.
• Energy & Utilities: overlaying sensor telemetry, maintenance records, grid schematics, and regulatory documentation.
• Engineering: cross-referencing simulation outputs, CAD files, inspection imagery, and technical specifications.
• Finance: reasoning across structured financial data, contract text, market feeds, and compliance filings.

Not seeing your specific domain or use case?

Lium is built to interpret and provide industry-specific POV in its answer engine, meaning it works for ANY company that requires a blended interpretation of various datasets. Get started for free to see its complex reasoning and accuracy yourself.

Since Lium’s AI uses one anchor point to provide multimodal answers directly using your files in their original format, you get prompt, fully accurate responses and not “educated guesses” that often come with ad hoc analysis from generic models. Your integrated data layer provides the deep industry knowledge your advanced industry requires; Lium makes it simple to extract insights from your large, complex datasets.

When you sign up for Lium for free, you’ll get to experience this highly accurate approach to multimodality for yourself. Get started today!

What is Multimodality?

Multimodality is a system’s ability to process and interpret data points from various file formats such as text, images, audio, and video, simultaneously in an overlaid capacity.

Just like human cognition allows people to integrate multiple senses when navigating the world, multimodal artificial intelligence is able to “read” text, “view” imagery, and “hear” audio by processing various files. Once integrated, it interprets these files multimodally to provide cohesive, domain-specific understanding of complex industries.

Is It Safe to Share Proprietary Data With Multimodal AI?

It's no secret that the generic AI platforms often train on the data that users share. When you spend thousands of dollars and countless hours collecting proprietary data, it needs to be yours alone.

With Lium, any data integrated into your organization’s environment remains your own. Relevant departments at your industry can get multimodal responses from the answer engine without the risk of your data being exposed to competitors or to train models.

Can Multimodal AI Be Used by Enterprise Teams?

Yes, any datasets processed and integrated into your Lium environment can be made accessible organization-wide. Engineers can ask for highly advanced calculations in seconds, while executives turn to it to help make accurate, data-backed high-level decisions.