Innodata Inc. (INOD) Q1 2026 Earnings Call

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WEBVTT 00:00:00.031 -- 00:00:03.352 on our call today for 00:00:04.756 -- 00:00:10.241 the large $51 million contract. We're providing what's called pre-training, 00:00:10.241 -- 00:00:16.107 mid-training, and post-training data. Soon we anticipate providing evals 00:00:16.107 -- 00:00:20.630 as well. And you can think of those as all 00:00:23.014 -- 00:00:27.599 classifications of data that's required in order to 00:00:27.599 -- 00:00:33.428 train and fine tune large language models. 00:00:33.631 -- 00:00:38.717 In terms of one of the other customers we talked about, we're providing 00:00:38.717 -- 00:00:40.339 trust 00:00:40.339 -- 00:00:43.664 and safety services. We're evaluating models. 00:00:43.664 -- 00:00:48.350 We're testing them. We're isolating areas where they're underperforming. 00:00:48.350 -- 00:00:54.135 We're prescribing the data mixes that are required in order to mitigate that performance. 00:00:55.533 -- 00:00:57.014 Similarly, 00:00:57.014 -- 00:01:02.880 another one of the wins that we talked about, or the soon-to-be wins, 00:01:02.880 -- 00:01:09.046 scaled data generation, large-scale data to train and improve models, 00:01:09.046 -- 00:01:13.190 testing for alignment with responsible AI. 00:01:13.190 -- 00:01:15.553 We're getting into 00:01:15.553 -- 00:01:19.497 creating data sets that are required for physical AI. 00:01:19.497 -- 00:01:24.399 You can think of physical AI as embodied intelligence or robots. 00:01:24.963 -- 00:01:30.149 So it's really along the full spectrum of capabilities that 00:01:30.149 -- 00:01:34.975 are required by the foundation model builders from a data perspective in order to support 00:01:34.975 -- 00:01:37.135 their products. 00:01:38.920 -- 00:01:43.022 That's great. Thank you so much. 00:01:43.926 -- 00:01:48....