TileDB

TileDB is foundational software designed by scientists for scientific discovery.

[TileDB @tiledb]

A patient isn't a row in a database; it's demographics, clinical notes, imaging, time-series vitals and genomic sequences combined.

Each modality demands different storage & query patterns. Multimodal data is a design problem before it's an analysis one.

https://t.co/Qc94EAXaET

[TileDB @tiledb]

Years of pharma research live in scattered documents that no AI agent can use.

That's the silo problem multimodal data platforms must solve, not work around.

📖 From 𝘔𝘶𝘭𝘵𝘪𝘮𝘰𝘥𝘢𝘭 𝘋𝘢𝘵𝘢 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮𝘴: 𝘈 2026 𝘉𝘶𝘺𝘦𝘳'𝘴 𝘎𝘶𝘪𝘥𝘦
https://t.co/n89BxesPiE

[TileDB @tiledb]

🎉 Couldn't imagine a better afternoon to top off #BioITWorld.

We brought R&D leaders to Boston's Seaport to make multimodal scientific data a substrate AI agents can find, access, and trust.

A heartfelt thanks to our co-hosts @TTECDigital and @Microsoft.

Until the next one!

[TileDB @tiledb]

In a competitive biopharma market, multimodal omics data powers innovation.

But the infrastructure and tools to work with it are usually built as separate stacks.

📖 From 𝘔𝘶𝘭𝘵𝘪𝘮𝘰𝘥𝘢𝘭 𝘋𝘢𝘵𝘢 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮𝘴: 𝘈 2026 𝘉𝘶𝘺𝘦𝘳'𝘴 𝘎𝘶𝘪𝘥𝘦
https://t.co/GHPMKY6xOs

[TileDB @tiledb]

@TTECDigital @Microsoft https://t.co/fgvGA4jXxb

[TileDB @tiledb]

Gearing up for #BioITExpo in Boston next week. Wednesday, we're hosting a reception in the Seaport with @TTECDigital + @Microsoft.

George Llado, veteran pharma technologist & TileDB board member, will be joining us to discuss multimodal scientific data AI-readiness.

RSVP 👇

[TileDB @tiledb]

Petabytes of imaging, genomic, and clinical data — and every new modality forces a rebuild.

The question isn't whether you have enough data. It's whether your architecture can query it where it lives.

Read the complete guide 👇
https://t.co/KXGeDvBGJZ

[TileDB @tiledb]

Multiomics advances. Getting insights to the bedside in real time is a different problem. That gap isn't purely scientific. It's a data infrastructure one.

📖 Quote from 𝘔𝘶𝘭𝘵𝘪𝘮𝘰𝘥𝘢𝘭 𝘋𝘢𝘵𝘢 𝘗𝘭𝘢𝘵𝘧𝘰𝘳𝘮𝘴: 𝘈 2026 𝘉𝘶𝘺𝘦𝘳'𝘴 𝘎𝘶𝘪𝘥𝘦
https://t.co/hrtBxaUIUu

[TileDB @tiledb]

Are you 𝘪𝘯 𝘵𝘩𝘦 𝘬𝘯𝘰𝘸? We think you should be.

@TileDB, @TTECDigital and @Microsoft are bringing together biopharma leaders at #BioITExpo — drinks, real conversation, multimodal data AI-ready.

Your agent's not invited. Promise.

📅 May 20 | Boston
https://t.co/SLEGpkiRyn

[TileDB @tiledb]

Multimodal AI has huge potential in healthcare — but scaling it faces real barriers: incompatible data formats, multiplying compute costs, modality bias, and explainability gaps that block regulatory approval.

Here's the full breakdown 👇
https://t.co/D8TfIIjZ4a

[TileDB @tiledb]

Multimodal AI, generative AI, and agentic AI increasingly overlap — but their core purposes differ.

One connects diverse data types. Another produces new outputs. A third acts autonomously. The distinctions shape your AI strategy.

Read more 👉 https://t.co/ill5f1ftGh

[TileDB @tiledb]

Your AI agent isn't invited. Promise.

At #BioITExpo? We're hosting a private cocktail reception with @TTECDigital and @Microsoft — a chance to connect with biopharma leaders tackling the challenge of making scientific data AI-ready.

📅 May 20 | Boston

https://t.co/Dp5qDueyhG

[TileDB @tiledb]

In healthcare, no single data source reveals the full picture.

Multimodal AI surfaces the connections — across genomics, clinical data, and patient records.

Read the complete guide on multimodal AI 👇https://t.co/i10SsafwaQ

[Front Line Genomics @FLGenomics]

Discover how TTEC Digital and TileDB are delivering cloud-native genomics data platforms to help life sciences organizations from Roberto Lleras’ (VP Healthcare & Life Sciences Solutions and Strategy, @TTECLife) at #FOGBoston. More info: https://t.co/fyKzZ7olE0

[TileDB @tiledb]

Most multimodal AI projects don't fail on the model — they fail on the data.

Incompatible file formats, inconsistent metadata across labs and vendors. The data exists — but can't be harmonized.

The complete 2026 guide to Multimodal AI 👇https://t.co/H1igiQI7GB

[TileDB @tiledb]

Not all multimodal datasets are equally accessible.

Some are open. Others need institutional approval or credentialed licenses — a detail that determines what's usable.

We mapped 15 — size, access model, and use case for each.

https://t.co/fSEDNb1Rjz

[TileDB @tiledb]

https://t.co/rvLuTzwW3W

[TileDB @tiledb]

Inconsistent metadata and incompatible file formats across imaging systems and electronic health records can hinder AI training in healthcare. Without expert-led curation pipelines, multimodal models risk learning from incomplete or mislabeled data.

https://t.co/KvhItcDKbE

[TileDB @tiledb]

Multimodal AI and agentic AI aren't the same thing.

Multimodal AI interprets data across modalities. Agentic AI plans, acts, and learns autonomously toward defined goals.

One expands what AI can perceive. The other decides what to do with it.

https://t.co/o5q8ydY2pq

[TileDB @tiledb]

At #HIMSS26, @TileDB, @TTECDigital, and @Microsoft brought HCLS leaders together for a cocktail reception. One theme dominated: the biggest barrier to scaling AI in healthcare isn't model capability — it's data infrastructure.

https://t.co/iwdvwbwzq7