INOD — what changed in the latest 10-Q
A section-by-section comparison of INOD's newest periodic SEC filing (10-K/10-Q) against the prior same-form filing: paragraphs added and removed per section, with verbatim excerpts. Purely a deterministic text diff — no similarity scores, no directional read, not investment advice.
Comparing 10-Q · 2026-05-07 vs the prior 10-Q · 2025-11-06
| Section | Outcome | Added | Removed | Minor | Unchanged |
|---|---|---|---|---|---|
| MD&A | Text added/removed | +39 | −94 | ~16 | 18 |
| Controls & procedures | Text added/removed | 0 | 0 | ~3 | 0 |
| Other information | Text added/removed | 0 | 0 | ~1 | 0 |
Counts are paragraphs; added/removed means text added or removed vs the prior filing — no direction or judgement implied.
Not shown (absent or not faithfully extractable): Market risk (Item 3), Legal proceedings, Risk factors
Representative excerpts
Up to 5 excerpts of about 300 characters per section, quoted verbatim from the two SEC filings.
MD&A
Text added vs the prior filing · source: 10-Q · 2026-05-07
Innodata Inc. (Nasdaq: INOD) (together with its subsidiaries, the “Company”, “Innodata”, “we”, “us” or “our”) is a global data engineering and AI systems services company that supports the development, training, post-training, evaluation, and deployment of advanced artificial intelligence systems. W…
Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We believe that AI will increasingly function as a foundational layer of the digital economy - …
Innodata was founded more than 35 years ago on the principle that high-quality, well-structured data is essential to leading information-retrieval systems. In 2016-2017, we began building proprietary AI language models based on then-emerging research and frameworks and integrating them into our data…
Today, leading AI innovation labs and Big Tech companies (including five of the so-called “Magnificent Seven”) building frontier generative AI models and leading enterprises engage us to provide (i) training and post-training data development; (ii) alignment and preference optimization; (iii) capabi…
We believe Innodata is differentiated by: (i) our ability to operate across the AI lifecycle in alignment with AI developers’ internal development and deployment pipelines; (ii) our scale of specialized human expertise; (iii) purpose-built platforms and processes that combine automation with rigorou…
Text removed vs the prior filing · source: 10-Q · 2025-11-06
Innodata Inc. (Nasdaq: INOD) (including its subsidiaries, the “Company,” “Innodata,” “we,” “us” or “our”) is a leading data engineering company. Our mission is to help the world’s most prestigious companies deliver the promise of ethical, high-performing artificial intelligence (“AI”), which we beli…
Innodata was founded on a simple idea: engineer the highest quality data so organizations across broad industry segments could make smarter decisions. Today, we believe we are delivering the highest quality data for some of the world’s most innovative technology companies to use to train the AI mode…
AI holds the promise that computers can perceive and understand the world, enabling products and services that would have been previously unimaginable and impossible with traditional coding. AI learns from data, and the highest-performing AI will have learned from the highest-quality data. We believ…
We are also helping companies deploy and integrate AI into their operations and products and providing innovative AI-enabled industry platforms, helping ensure that our customers’ businesses are prepared for a world in which machines augment human activity in ways previously unimaginable.
We developed our capabilities and honed our approaches progressively over the last 35+ years creating high-quality data for many of the world’s most demanding information companies. Approximately nine years ago, we formed Innodata Labs, a research and development center, to research, develop and app…
How to read Risk Factors (Item 1A) in a 10-Q
A 10-Q risk-factor section usually takes one of three forms; this page classifies it as one of:
- Pointer — the filer states there have been no material changes and points back to the annual 10-K risk factors; there is no own risk text to compare this quarter.
- Partial update — the filer carves out specific updated risks ("except as set forth below"); the excerpts show exactly what is new this quarter.
- Restated in full — the quarter carries the complete risk-factor text. When the prior quarter was only a pointer there is no prior full text to diff against, so the page flags the section as restated instead.
This describes the filing structure only — it is never a judgement on whether risk went up or down.
Source: text-level diff of the two SEC EDGAR filings · deterministic (no AI-generated content) · for reference only · not investment advice