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Innodata Q2 Earnings Call Focuses on AI Research and Diversification
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Key Takeaways
Innodata posted 58% Q2 revenue growth as its largest customer fell to 37% of sales from 56% in Q1.
INOD reiterated 40% 2026 revenue growth guidance while excluding several large potential engagements.
Innodata is expanding agentic AI, model evaluation, cybersecurity and physical-AI programs.
Innodata Inc. (INOD - Free Report) used its second-quarter 2026 earnings call to emphasize broader customer diversification, expanding AI research capabilities and a disciplined approach to revenue guidance. Chairman and CEO Jack Abuhoff also outlined a planned CEO transition as the company scales.
The quarter combined 58% year-over-year revenue growth with a 49% adjusted gross margin. President and chief revenue officer Rahul Singhal highlighted new programs spanning agentic AI, model evaluation, cybersecurity and physical AI.
INOD Broadens Its Customer Base
Abuhoff said that Innodata’s largest customer represented 37% of second-quarter revenues, down from 56% in the first quarter. A Big Tech customer announced last quarter rose to 34% of revenues from 17%.
Abuhoff said that the largest customer generated less revenue sequentially because of changes in program structure and service mix, while he still expects that customer’s full-year revenues to increase year over year.
Abuhoff also pointed to the addition of a new frontier-lab customer, emphasizing that Innodata is broadening both its customer base and the number of programs it supports.
Innodata Keeps Guidance Disciplined
Abuhoff reiterated guidance for full-year 2026 revenue growth of 40% or more. He said that several large potential engagements with existing and new customers are excluded from the forecast.
Abuhoff said that those programs will enter the forecast only after Innodata has fully won the business and can determine the timing of revenue recognition.
A Craig-Hallum analyst pressed for detail on the excluded opportunities. Abuhoff said that the pipeline spans frontier-model, enterprise and government work, with agentic AI prominent among current opportunities.
INOD Turns Research Into Commercial Programs
Singhal said that research and innovation are becoming a growth engine across pre-training, post-training, model evaluation and benchmarking. He highlighted new work in long-horizon agent personalization and reinforcement-learning environments for computer-use agents. Singhal also said that Innodata released two public benchmarks designed to identify model failure modes and support follow-on data-generation work.
Singhal said that the company is also developing physical-AI capabilities through robotics data collection and a planned motion-capture lab, with successful pilots moving discussions toward enterprise-scale multimodal programs.
Innodata Links Mix to Margin Expansion
The company reported second-quarter revenues of $92.1 million, up 58% year over year and 2% sequentially. The metric beat the Zacks Consensus Estimate of $86.3 million. Reported earnings of $0.41 per share topped the consensus estimate of $0.21.
CFO Jayant Chauhan said that adjusted gross margin reached 49%, two percentage points above the first quarter and nine points above management’s 40% target. Adjusted EBITDA was $25.4 million, or 27.5% of revenue.
A Maxim Group analyst asked whether the richer margin profile should persist. Abuhoff said that strategic initiatives should improve revenue quality over time, but quarterly margins can fluctuate if Innodata wins large projects with lower gross margins.
INOD Adds Cyber, Federal and Enterprise Paths
Singhal said that Innodata released the first stage of its AI Cyber Training Suite, including 12 datasets and evaluation systems focused on secure coding and vulnerability repair by AI agents.
In Q&A, a Craig-Hallum analyst asked about federal opportunities. Abuhoff said that Innodata is discussing partnerships with government agencies and sees evaluation, benchmarking and red-teaming work as areas of opportunity.
Abuhoff also said that enterprise adoption of agentic AI is creating demand for assurance capabilities tied to the research platform Innodata uses with frontier-model customers.
Innodata Prepares for Leadership Transition
Abuhoff said that Singhal will become president and CEO on Sept. 30, while he will move to executive chairman and focus on research-enabled enterprise and federal opportunities.
Singhal said he plans to build on Innodata’s research-driven strategy. Chauhan’s expanded remit includes capital allocation, capital markets, customer partnerships and potential M&A.
The earnings call left research-led expansion, customer diversification and disciplined treatment of pipeline opportunities as Innodata’s central priorities heading into the second half.
Zacks Style Scores complement the Zacks Rank, with A and B grades representing stronger characteristics for their respective styles. INOD, therefore, pairs a favorable Zacks Rank with mixed Style Score signals. The Zacks Rank can change as earnings estimates are revised following the just-reported results.
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Innodata Q2 Earnings Call Focuses on AI Research and Diversification
Key Takeaways
Innodata Inc. (INOD - Free Report) used its second-quarter 2026 earnings call to emphasize broader customer diversification, expanding AI research capabilities and a disciplined approach to revenue guidance. Chairman and CEO Jack Abuhoff also outlined a planned CEO transition as the company scales.
The quarter combined 58% year-over-year revenue growth with a 49% adjusted gross margin. President and chief revenue officer Rahul Singhal highlighted new programs spanning agentic AI, model evaluation, cybersecurity and physical AI.
INOD Broadens Its Customer Base
Abuhoff said that Innodata’s largest customer represented 37% of second-quarter revenues, down from 56% in the first quarter. A Big Tech customer announced last quarter rose to 34% of revenues from 17%.
Abuhoff said that the largest customer generated less revenue sequentially because of changes in program structure and service mix, while he still expects that customer’s full-year revenues to increase year over year.
Abuhoff also pointed to the addition of a new frontier-lab customer, emphasizing that Innodata is broadening both its customer base and the number of programs it supports.
Innodata Keeps Guidance Disciplined
Abuhoff reiterated guidance for full-year 2026 revenue growth of 40% or more. He said that several large potential engagements with existing and new customers are excluded from the forecast.
Abuhoff said that those programs will enter the forecast only after Innodata has fully won the business and can determine the timing of revenue recognition.
A Craig-Hallum analyst pressed for detail on the excluded opportunities. Abuhoff said that the pipeline spans frontier-model, enterprise and government work, with agentic AI prominent among current opportunities.
INOD Turns Research Into Commercial Programs
Singhal said that research and innovation are becoming a growth engine across pre-training, post-training, model evaluation and benchmarking. He highlighted new work in long-horizon agent personalization and reinforcement-learning environments for computer-use agents. Singhal also said that Innodata released two public benchmarks designed to identify model failure modes and support follow-on data-generation work.
Singhal said that the company is also developing physical-AI capabilities through robotics data collection and a planned motion-capture lab, with successful pilots moving discussions toward enterprise-scale multimodal programs.
Innodata Links Mix to Margin Expansion
The company reported second-quarter revenues of $92.1 million, up 58% year over year and 2% sequentially. The metric beat the Zacks Consensus Estimate of $86.3 million. Reported earnings of $0.41 per share topped the consensus estimate of $0.21.
Innodata Inc Price, Consensus and EPS Surprise
Innodata Inc price-consensus-eps-surprise-chart | Innodata Inc Quote
CFO Jayant Chauhan said that adjusted gross margin reached 49%, two percentage points above the first quarter and nine points above management’s 40% target. Adjusted EBITDA was $25.4 million, or 27.5% of revenue.
A Maxim Group analyst asked whether the richer margin profile should persist. Abuhoff said that strategic initiatives should improve revenue quality over time, but quarterly margins can fluctuate if Innodata wins large projects with lower gross margins.
INOD Adds Cyber, Federal and Enterprise Paths
Singhal said that Innodata released the first stage of its AI Cyber Training Suite, including 12 datasets and evaluation systems focused on secure coding and vulnerability repair by AI agents.
In Q&A, a Craig-Hallum analyst asked about federal opportunities. Abuhoff said that Innodata is discussing partnerships with government agencies and sees evaluation, benchmarking and red-teaming work as areas of opportunity.
Abuhoff also said that enterprise adoption of agentic AI is creating demand for assurance capabilities tied to the research platform Innodata uses with frontier-model customers.
Innodata Prepares for Leadership Transition
Abuhoff said that Singhal will become president and CEO on Sept. 30, while he will move to executive chairman and focus on research-enabled enterprise and federal opportunities.
Singhal said he plans to build on Innodata’s research-driven strategy. Chauhan’s expanded remit includes capital allocation, capital markets, customer partnerships and potential M&A.
The earnings call left research-led expansion, customer diversification and disciplined treatment of pipeline opportunities as Innodata’s central priorities heading into the second half.
Zacks Signals for INOD
INOD currently carries a Zacks Rank #2 (Buy). Its Growth Score is A, while it has a Value Score of F, a Momentum Score of F and a VGM Score of D. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
Zacks Style Scores complement the Zacks Rank, with A and B grades representing stronger characteristics for their respective styles. INOD, therefore, pairs a favorable Zacks Rank with mixed Style Score signals. The Zacks Rank can change as earnings estimates are revised following the just-reported results.