Innodata

Innodata drives leading AI with 36+ years of data expertise. 🧠 That’s why seven of the world’s largest tech companies trust Innodata for their AI initiatives.

[Innodata @innodata]

Language AI got its food for free.

Robots got nothing.

Training Physical AI means deliberately creating data in the real world, from first-person demonstrations and motion data to retargeting, teleoperation, and contextual safety evaluation.

Read more: https://t.co/Egv5WxVJUi

[Innodata @innodata]

An AI agent can perform well in a demo and still fail inside an enterprise workflow.

The difference often comes down to workflow fit:

Does the agent have the right context? Clear decision boundaries? Access to the right systems? Defined controls and escalation paths? A measurable standard for success?

Our latest article outlines six questions enterprises should answer before moving an AI agent into production.

Read here: https://t.co/TKNIyAdhOx

[Innodata @innodata]

Most AI benchmarks test models on short, isolated tasks.

But that is not how AI systems are used in practice.

Interactions are long, messy, and multimodal. Users revise instructions. Important details are buried in documents, images, or prior turns. Context carries across the full conversation.

Innodata’s Long Context & Complex Interaction (LCCI) Benchmark is designed to evaluate how AI models perform under those conditions.

In our latest article, we share preliminary findings from LCCI and explore why long-context LLM evaluation needs to look beyond aggregate scores and toward the specific failure modes that matter in real-world model performance.

The article also links to our public preview dashboard, where readers can explore the benchmark results interactively.

Read more: https://t.co/NvAQGKmPJv

[Innodata @innodata]

Innodata is pleased to announce the appointment of Jayant Chauhan as Executive Vice President and Chief Financial Officer, effective July 6, 2026.

Jayant brings more than two decades of experience building and leading finance functions for fast-growing global technology companies.

Read the full announcement: https://t.co/UXBLruzk8G

[Innodata @innodata]

The Innodata GenAI Summit is happening this week in London 🏙️

On May 21, we’ll bring together AI builders, researchers, executives, and technical leaders for a focused day on the systems, infrastructure, and deployment challenges shaping AI today.

The conversations will span world models, autonomous systems, physical AI, evaluation, safety, infrastructure, and what it takes to bring advanced AI systems into production.

We're looking forward to an incredible day in London with leaders from across the AI ecosystem.

📍 London
📅 May 21, 2026
🔗 Register: https://t.co/OHIQ0HN0eu

[Innodata @innodata]

LLMs may know cultural facts, but can they apply cultural understanding when context is implied? 🌎

We’re sharing findings from the Innodata Cultural Alignment Benchmark (ICAB), a multimodal evaluation built to assess how well LLMs understand culture beyond surface-level knowledge.

ICAB examines whether models can navigate implicit cultural context across languages, locales, and real-world scenarios, from workplace norms to family dynamics to culturally specific visual prompts.

The results point to a clear gap: models perform better when cultural expectations are explicit, but struggle when they need to infer nuance from context.

Read the blog and explore the interactive results dashboard here: https://t.co/ybdr6RHIYM

#AI #LLMs #CulturalAlignment #ResponsibleAI #AIResearch #MultimodalAI

[Innodata @innodata]

Exciting news for Innodata Federal 🇺🇸

We’re thrilled to announce that Innodata Federal has been accepted into the CDAO Tradewinds platform as an awardable entity- meaning we’re now eligible to receive and deliver AI-driven projects directly through this prestigious federal marketplace.

This milestone marks a significant step forward in expanding how we support government agencies with mission-critical AI solutions- faster, more efficiently, and at scale.

Explore what we’re building in federal AI: https://t.co/M97k2v5R02

[eMerge Americas @eMergeAmericas]

We’re proud to welcome Innodata as a Diamond Sponsor of #eMergeAmericas 2026! 🌟

@innodata is a global data engineering and AI solutions company that helps businesses build, train, and deploy artificial intelligence systems.

Learn more ➡️ https://t.co/LaABZtkzLG

#globaltech #floridatech #tech

[Innodata @innodata]

AI doesn’t always pick the best answer.
In fact, it often settles for “good enough.”

Why? Because in large systems, the sheer volume of average options can overwhelm truly high-quality ones.

In our latest article, Innodata’s Senior AI Researcher Esther Derman unpacks this hidden problem and explains how new approaches in reinforcement learning are helping rebalance exploration and precision.

Drawing on her research presented at ICLR, she shows how AI systems can move beyond proxy-driven results toward real-world performance.

Read more: https://t.co/REKSB3UU6S

[Innodata @innodata]

Innodata is proud to join @eMergeAmericas as a Diamond Sponsor.

As AI continues to evolve, the conversation is shifting beyond models toward what it takes to build systems that actually perform in real-world environments. Data quality, evaluation, and infrastructure are becoming the defining factors.

Join Us in Miami, FL | April 22-24, 2026
https://t.co/cPkXqApq1q

[Innodata @innodata]

AI can count aircraft from space.
But understanding them is a very different problem.

In our latest article, Innodata’s Frank Tanner explores what happens when leading multimodal AI models are applied to satellite imagery, and where they fall short. While models perform well at counting objects, they struggle with classification tasks that require real-world context like scale, geometry, and physics.

The takeaway: today’s AI is powerful, but it still lacks something fundamental — a true “world model.”

This gap has real implications for defense, geospatial intelligence, and any application where physical understanding matters.

Read the full blog to see what this means for the future of AI: https://t.co/M02ULBCpxa

[Innodata @innodata]

A quick look at who you’ll hear from at Innodata's GenAI Summit in London this May:

→ Microsoft
→ Amazon
→ Databricks
→ American Express
→ Huawei

Industry leaders building, deploying, and scaling AI systems today.

May 21 → Register now: https://t.co/1EuCwh2Xid

[Innodata @innodata]

Innodata will be at eMerge Americas in Miami this month 🚀 🌴

Rahul Singhal, President + Chief Revenue Officer, is speaking on the AI + Deep Tech stage about how organizations are building and deploying agentic AI systems, and what that shift means for enterprise technology.

📍 Agentic AI in Action: Architecting Autonomous Systems
🗓 April 24, 2026
🕛 12:00 – 12:45 PM
Register: https://t.co/cPkXqApq1q

Join the conversation around where autonomous AI is headed next.

[Innodata @innodata]

Most AI events talk about what’s possible.

This one is about what’s actually working.

At the Innodata GenAI Summit, you’ll hear from teams:

→ deploying world models
→ building agentic systems
→ solving safety, evaluation, and infrastructure challenges

Join us in London → https://t.co/gZlzNP6cfX

[Innodata @innodata]

Physical AI depends on more than better models. It depends on better data.

Systems don’t fail because they can’t see. They fail because they can’t interpret context and decide what matters.

A plate isn’t just a plate. It’s dirty, clean, or already put away, and each state requires a different action.

That’s the gap.

Better models alone won’t fix it. Better data will.

We break it down here in our latest article: https://t.co/Yh1NF5SQ8S

[Innodata @innodata]

We’re bringing the Innodata GenAI Summit to London.

On May 21, we’ll convene leaders building and deploying AI systems across:
• world models
• agentic systems
• evaluation, safety, and infrastructure

This is a focused, single-day event designed for teams working at the model and system level, not high-level overviews.

Expect technical keynotes, candid discussions, and a room of peers operating in similar environments.

📍 London • May 21, 2026

🔗 Register: https://t.co/gZlzNP6cfX

[Innodata @innodata]

AI systems often perform well in testing but fail in the real world.

Why? Blind spots.

Edge cases, biased data, and evaluation gaps can create hidden weaknesses that only appear after deployment.

Read how enterprises can detect them: https://t.co/frSiiA29fA

[Innodata @innodata]

You can’t govern agentic AI by looking only at the final answer.

The real signal is in the trace: decisions, retries, tool usage, and recovery steps that lead to an outcome.

Check out our latest article on how trace datasets enable automated evaluation and enterprise-grade governance for agentic AI systems.

Read it here 👇
https://t.co/djqI1WX02I

[Innodata @innodata]

Human motion is not just pixels over time. It follows physics.

In our latest article, Frank Tanner, Innodata’s VP of Computer Vision and Robotics, shows how kinematics-based motion analysis improves data labeling, flags annotation errors automatically, and helps evaluate whether models are tracking movement realistically.

This approach closes the loop between labels, models, and quality control, especially for motion-driven use cases.

Read the article here: https://t.co/BKhsdQzXW6

[Innodata @innodata]

Innodata announced that it has been selected by @PalantirTech to provide training data and data engineering services supporting AI-enabled platforms for rodeo event analysis.

The engagement includes specialized annotation and multimodal data engineering to support computer vision models used for automated performance metrics across rodeo events.

Read the full press release: https://t.co/0Ih79P6U6Y