Innodata drives leading AI with 36+ years of data expertise. š§ Thatās why seven of the worldās largest tech companies trust Innodata for their AI initiatives.
The Innodata GenAI Summit is happening this week in London šļø
On May 21, weāll 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.
š London
š May 21, 2026
š Register: https://t.co/OHIQ0HN0eu
LLMs may know cultural facts, but can they apply cultural understanding when context is implied? š
Weāre 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
Exciting news for Innodata Federal šŗšø
Weāre thrilled to announce that Innodata Federal has been accepted into the CDAO Tradewinds platform as an awardable entity- meaning weāre 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 weāre building in federal AI: https://t.co/M97k2v5R02
Weāre proud to welcome Innodata as a Diamond Sponsor of #eMergeAmericas 2026! š
@innodata is a global data engineering and AI solutions company that helps businesses build, train, and deploy artificial intelligence systems.
Learn more ā”ļø https://t.co/LaABZtkzLG
#globaltech #floridatech #tech
AI doesnāt always pick the best answer.
In fact, it often settles for āgood enough.ā
Why? Because in large systems, the sheer volume of average options can overwhelm truly high-quality ones.
In our latest article, Innodataās 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 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
AI can count aircraft from space.
But understanding them is a very different problem.
In our latest article, Innodataās 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: todayās AI is powerful, but it still lacks something fundamental ā a true āworld model.ā
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
A quick look at who youāll hear from at Innodata's GenAI Summit in London this May:
ā Microsoft
ā Amazon
ā Databricks
ā American Express
ā Huawei
Industry leaders building, deploying, and scaling AI systems today.
May 21 āĀ Register now: https://t.co/1EuCwh2Xid
Innodata will be at eMerge Americas in Miami this month š š“
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.
š Agentic AI in Action: Architecting Autonomous Systems
š April 24, 2026
š 12:00 ā 12:45 PM
Register: https://t.co/cPkXqApq1q
Join the conversation around where autonomous AI is headed next.
Most AI events talk aboutĀ whatāsĀ possible.
This one is aboutĀ whatāsĀ actually working.
At the Innodata GenAI Summit,Ā youāllĀ hear from teams:
ā deploying world models
ā building agentic systems
ā solving safety, evaluation, and infrastructure challenges
Join us in London ā https://t.co/gZlzNP6cfX
Physical AI depends on more than better models. It depends on better data.
Systems donāt fail because they canāt see. They fail because they canāt interpret context and decide what matters.
A plate isnāt just a plate. Itās dirty, clean, or already put away, and each state requires a different action.
Thatās the gap.
Better models alone wonāt fix it. Better data will.
We break it down here in our latest article:Ā https://t.co/Yh1NF5SQ8S
WeāreĀ bringing the Innodata GenAI Summit to London.
On May 21,Ā weāllĀ conveneĀ leaders building and deploying AI systems across:
⢠world models
⢠agentic systems
⢠evaluation, safety, and infrastructure
This is a focused, single-dayĀ eventĀ designed for teams working at the model and system level,Ā not high-level overviews.
Expect technical keynotes, candid discussions, and a room of peersĀ operatingĀ in similar environments.
š London ⢠May 21, 2026
š Register: https://t.co/gZlzNP6cfX
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
You canāt 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 š
https://t.co/djqI1WX02I
Human motion is not just pixels over time. It follows physics.
In our latest article, Frank Tanner, Innodataās 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 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
If your AI is learning every day, your evaluation strategy canāt be static.
Models that perform well in demos can quietly drift in production, introducing bias, risk, or compliance issues over time. Thatās why AI evaluation must be continuous, not a one-time test.
In our latest blog, we break down the 7 core components enterprises must get right to keep AI systems accurate, fair, secure, and trustworthy.
š Read the full article here: https://t.co/0JQbXcPIUs
Innodata has been awarded a prime contract position on the U.S. Missile Defense Agencyās Scalable Homeland Innovative Enterprise Layered Defense (SHIELD) IDIQ program.
This selection positions Innodata to compete for future task orders supporting research, development, engineering, prototyping, and operations for critical Missile Defense Agency systems.
Read the full press release here: https://t.co/HAs3GwSHN6
As unmanned aerial vehicles become more common, reliably detecting and tracking them in real-world conditions has become a critical computer vision challenge.
In this post, Frank Tanner, Innodataās VP of Computer Vision and Robotics, shares results from evaluating Innodataās UAV tracking pipeline on the Anti-UAV benchmark, one of the most widely used public datasets in this space. The results highlight strong performance across accuracy, precision, and robustness, with flexibility for real-world deployment across different sensors and operational requirements.
Read the full post to learn how benchmark performance translates into practical UAV tracking systems. š https://t.co/qW2vRnd2qd
A quick look back at the Innodata GenAI Summit in San Francisco š„
Check out the highlights and explore full sessions on our site āĀ https://t.co/4klnBJKChV