TipRanks Smart Growth Portfolio #16: Truth Miners
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Dear Investors,
Welcome to the 16th edition of the Smart Growth Portfolio and Newsletter.
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Portfolio News
❖ Monday.com (MNDY) continues to show healthy demand signals despite a mixed macro backdrop for enterprise software. According to Citi, digital footprint data indicates that top-of-funnel activity – early-stage engagement such as website traffic and inbound interest – remains solid. While its peers are facing visibility challenges due to AI-driven shifts in search engine behavior, Monday has held up thanks to a “relatively aggressive” marketing posture, which Citi sees as a positive leading indicator. Although Citi pointed to some pressure on net revenue retention in recent months, it reiterated MNDY’s “Buy” rating and top-pick status, citing a fairly stable overall demand environment.
Meanwhile, Morgan Stanley initiated coverage with a “Hold” rating and a $330 price target, calling Monday’s move toward enterprise accounts, multi-product expansion, and a sales-led growth model “a large and compelling opportunity.” The firm acknowledged execution risk in the transition – but believes Monday can manage it successfully. Earlier, Wells Fargo lifted its price target from $335 to $365, maintaining a “Buy” rating. The upgrade was based on improving seasonal software buying patterns and easing macro pressure heading into the second half of 2025.
Monday.com also named Harris Beber, former global head of marketing for Google Workspace, as its new Chief Marketing Officer. Beber helped launch and scale AI-powered features across Google’s productivity suite – a background that aligns closely with Monday’s own AI product roadmap and enterprise ambitions. His hire underscores the company’s commitment to accelerating adoption among larger customers and differentiating through intelligent workflows.
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❖ Backblaze (BLZE) continues to differentiate itself on cost and performance in the crowded cloud storage market. A newly released independent report from Enterprise Strategy Group (ESG) found that B2 Cloud Storage delivers up to 3.2× lower total cost of ownership compared to traditional cloud providers. The analysis highlighted key savings such as a 56% reduction in monthly storage costs and 100% savings on download and transaction fees – a major draw for customers struggling with egress costs from larger platforms. ESG also noted that organizations using B2 could cut time spent managing data by over 90%, with substantial migration savings for both on-prem and cloud-to-cloud transitions. The report covered a range of use cases – from AI model storage to backup and ransomware protection.
B2’s economic efficiency is reinforced by real-world results. Media post-production firm IDC LA recently reported a 75% reduction in off-site storage costs after implementing B2 as its nearline archive solution. Using Backblaze’s S3-compatible API, IDC LA achieved nightly backups and greater disaster resilience – all while reducing strain on its on-prem infrastructure. Leadership at the company cited predictable pricing and high availability as critical advantages. Combined with ESG’s findings, the IDC LA case positions BLZE as a credible challenger in cloud storage – offering transparent, scalable alternatives at materially lower cost.
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❖ Alkami (ALKT) shares rose after JPMorgan reiterated its “Buy” rating, even while trimming its price target from $45 to $40 – still implying more than 40% upside from current levels. The lowered target reflects a more conservative near-term outlook, likely tied to broader market sentiment rather than company-specific concerns. JPMorgan’s note remained highly constructive, highlighting Alkami’s strong customer retention, long contract durations that support revenue visibility, and favorable positioning in the digital banking sector.
The firm estimates the addressable market for modern digital banking platforms at roughly $10 billion. Alkami currently holds less than 5% of that, leaving significant room for share gains. JPMorgan sees Alkami’s enterprise-grade platform as a strong candidate to displace legacy vendors and capture long-term growth in a fast-evolving segment.
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Portfolio Updates
❖ We are keeping PowerFleet (AIOT) under review following its June 17 filing delay notice and the June 18 release of full-year FY2025 financials – which, while unaudited, showed strong performance.
The 10-K filing delay stems from additional work required on financial statement disclosures and internal control assessments, not from restatements, fraud, or missed targets. This is not the first time AIOT has taken advantage of a 12b-25 extension, and there is no indication of deeper issues. That said, the company now has until July 1 to file – and we’ll be watching for timely compliance.
Despite the delay, Powerfleet delivered what it promised: full-year FY25 revenue of $362.5 million – up approximately 170% YoY – with ~75% coming from SaaS, and adjusted EBITDA of $71 million, representing a tenfold increase from the prior year. The company beat every key synergy, customer, and profitability goal outlined at the time of the MiX and Fleet Complete deals. FQ4 results showed 49% YoY growth in service revenue, gross margins above 60%, and a sharp rise in EBITDA. Retention improved for a third consecutive quarter, and cross-sell momentum is clearly building.
The market responded accordingly: AIOT stock rose sharply on June 18, a day after the 10-K delay was disclosed – signaling that investors interpreted the delay as administrative, not structural. With strong customer commentary, marquee wins, and sustained cost discipline, the core thesis remains intact: Powerfleet is executing on its platform unification and SaaS scaling plan.
We continue to see long-term potential here. But as always, we’re watching execution: the timely filing of the 10-K, successful pipeline conversion, and sustained margin expansion in FY26 will all be important milestones. For now, the story looks credible – and very much on track.
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❖ We are keeping GitLab (GTLB) under review after its cautiously positive Q1 results and modest guidance. While the stock dipped on revenue forecast that looked “just‑okay,” the fundamentals remain rock-solid. Q1 again beat estimates, with non‑GAAP EPS of $0.17 (+467% YoY) and free cash flow nearly tripling, plus gross margins sitting at ~89%. ARR momentum continues, especially in enterprise accounts, with upgrades tied to AI/DevSecOps roadmaps.
No new filings or material updates since last week – but Wells Fargo just flagged GitLab as one of the key beneficiaries of the shift toward agentic AI, citing its platform advantage in AI orchestration and security. Analyst ratings still lean positive, with multiple “Buys” and average upside in the 40-50% range.
Bottom line: The stock may have been oversold on thin beats, but renewed sentiment – driven by AI tailwinds and consistent execution – suggests the long-term story remains intact. We’re watching for validation through continued ARR acceleration and AI rollout progress.
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This Week’s Top Growth Pick: Innodata (INOD)
Innodata Inc. is an AI data services company that builds, labels, and structures high-quality datasets to train, fine-tune, and validate enterprise-grade machine learning models. Its platform combines proprietary workflow software with a global human-in-the-loop workforce to deliver scalable annotation, taxonomy development, document structuring, and model evaluation. From generative AI to regulatory automation, Innodata supports clients in tech, finance, and healthcare where accuracy and explainability are mission-critical. What sets the company apart is its ability to ingest messy, unstructured information – PDFs, emails, reports, contracts – and transform it into machine-readable, model-ready formats. In a world racing to capitalize on LLMs, vector databases, and AI copilots, Innodata is quietly doing the dirty work: cleaning, labeling, aligning, and structuring the data that fuels intelligent systems.
Source: Innodata Q1 2025 Investor Presentation
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The AI Middleman
Founded in 1988, Innodata began as a content services provider, handling editorial and back-office document processing for publishers and government agencies. As enterprise digitalization accelerated in the 1990s and early 2000s, the company grew into a niche vendor for structuring and formatting large volumes of print-based content. But over the past five years, Innodata has undergone a significant reinvention – transforming itself into a data-centric AI enablement platform built for the age of machine learning models and LLMs.
The pivot began in earnest around 2019, as the company expanded from content conversion into structured data annotation, taxonomy development, and NLP-centric services. This shift laid the groundwork for its current focus: helping enterprise clients generate high-quality, model-ready datasets from unstructured, often messy information. In 2021, Innodata launched its proprietary platform, AI Annotation Factory, to automate labeling workflows while maintaining human-in-the-loop precision. This blend of automation and human oversight now underpins its cost efficiency and scalability.
In 2022 and 2023, Innodata deepened its push into AI by launching an AI Model Evaluation offering and announcing new business with “three of the world’s largest technology companies” – likely hyperscalers or LLM builders, though not named. The release of ChatGPT in late 2022 sparked a wave of demand for high-quality fine-tuning data, propelling Innodata into direct support roles for enterprise AI deployments. By mid-2023, it had launched DocAnalytics, a platform to extract structured insights from long-form business documents – a high-friction, high-value challenge in AI development.
The company also made targeted internal investments during this time. It rebuilt its software architecture using microservices and embedded traceability tools – crucial for clients in the financial services, insurance, and healthcare. In Q4 2023, it created a generative AI services division to support large enterprise adoption of LLMs, spanning dataset construction, evaluation loops, prompt engineering, and alignment refinement.
Unlike some peers, INOD hasn’t grown through headline-grabbing M&A. Its expansion has been focused and organic – compounding technical capabilities and deepening client relationships. From a legacy content processor to a next-gen data infrastructure partner, Innodata has repositioned itself at the core of one of the most valuable bottlenecks in the AI economy: high-quality, explainable, custom data.
Source: Innodata Q1 2025 Investor Presentation
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Stealth Provider
Innodata makes money by preparing, structuring, and managing the high-quality data that powers AI systems. Its core business is Digital Data Solutions (DDS) – representing 87% of total revenue in Q1 2025 – where it provides training data, annotation services, model evaluation, and AI deployment support to some of the world’s largest technology companies.
At the heart of this segment is its proprietary AI data annotation platform, which blends machine-assisted tagging with human-in-the-loop validation to deliver instruction datasets, reinforcement learning labels, and reward modeling pipelines for large language models. The platform is used for both classical and generative AI, across modalities including text, audio, video, and sensor data. Customers also rely on Innodata for synthetic data generation where real-world data is scarce or sensitive.
Beyond data preparation, INOD offers AI model deployment and integration services, helping enterprises fine-tune or customize foundation models for domain-specific tasks. These services span data transformation, compliance, consolidation, and hygiene – particularly valuable in financial, healthcare, and regulatory-heavy sectors.
The company’s Synodex and Agility segments contribute the remaining 13% of revenue, offering niche SaaS platforms in medical records digitization and public relations analytics, respectively. These platforms contribute recurring and semi-recurring revenue, with Agility operating as a high-margin subscription SaaS business for media and PR analytics, while Synodex leans more heavily on volume-based services for digitizing and structuring medical records. Together, they provide stable, complementary income streams outside the core AI services business.
What sets Innodata apart isn’t just its workflow software – it’s the domain-specific data expertise, rapid time-to-value, and auditability it offers customers building or deploying AI. Its combination of proprietary tools and managed services enables clients to outsource the most error-prone, labor-intensive parts of the model lifecycle without sacrificing control or explainability.
As for market size, Innodata is positioned in the AI data preparation and model evaluation layer, a niche projected to exceed $20-25 billion by 2027, driven by the explosion of fine-tuned enterprise LLMs, multimodal AI, and regulatory demand for model transparency. While the company’s precise share of this market is undisclosed, its hyperscaler customer base and recent growth imply that it commands a small but expanding footprint – with room to take share as enterprises seek vendor-neutral, high-integrity data partners amid growing scrutiny of AI pipelines.
Source: Innodata Q1 2025 Investor Presentation
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Crosscurrents and Catalysts
Innodata cleared a major hurdle this week. On June 18, the company announced that both the U.S. Department of Justice and the Securities and Exchange Commission had formally closed their investigations into its AI-related public disclosures without recommending any enforcement actions. That effectively removes the threat of regulatory penalties and puts to rest concerns about compliance failures – a material win for investor confidence.
But while the regulatory cloud has lifted, a separate securities class action lawsuit, filed in February 2024, remains active. The suit alleges that Innodata overstated its AI capabilities and misled shareholders about the depth of its technological differentiation. Innodata has denied the claims and filed a motion to dismiss in March 2025. That motion is still pending, with a ruling expected later this year. Even if the case proceeds, securities litigation typically unfolds over years – suggesting any potential liabilities are distant, uncertain, and unlikely to impact near-term operations.
Meanwhile, market dynamics are shifting in INOD’s favor. Meta’s investment in Scale AI raised red flags across the AI ecosystem, prompting concerns about vendor lock-in, data entanglement, and preferential access. At least one major AI player is reportedly exploring alternatives. Meanwhile, there is growing speculation in industry circles that Google, OpenAI, and xAI may reassess their reliance on Scale amid Meta’s deepening involvement. This creates a rare opening for neutral providers like Innodata to position themselves as independent, enterprise-focused partners – especially for clients in regulated industries who demand explainability, data governance, and operational separation from Big Tech.
Still, Innodata isn’t a large-cap incumbent. It remains a small player in a fragmented market, with relatively high customer concentration and a growth plan that hinges on deepening existing relationships and automating its service stack. Any stumbles in execution – technical, legal, or reputational – could slow momentum. Scale’s growing dominance, even with friction, remains a real competitive threat.
Yet the asymmetric setup is hard to ignore. INOD has emerged from regulatory review with a clean slate, is positioned to benefit from hyperscaler churn, and remains one of the few companies offering high-quality AI data services without ecosystem entanglements. For investors who can stomach some legal noise and market volatility, the upside isn’t just theoretical – it’s increasingly visible.
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Growth That Pays
Innodata is sustaining its high growth trajectory – and now, it’s profitable. In Q1 2025, the company posted $58.3 million in revenue, up 120% YoY, handily beating analyst expectations near $53 million. This marked its first quarter of GAAP profitability, with net income of $7.8 million – or EPS of $0.22, also far above estimates – compared to a $1 million profit a year earlier. Operating margins also showed material improvement: consolidated gross margin reached 39.8%, up from 36.4% a year ago, with the DDS segment delivering 38.8%, Agility 54.0%, and Synodex 27.4%.
On a non-GAAP basis, Innodata’s profitability is less formally tracked, but results indicate a clear improvement path. Though adjusted EBITDA isn’t broken out, stronger gross margins and controlled spending suggest the business is now generating healthy operating leverage. This is a major milestone for a company previously reliant on revenue growth without bottom-line traction.
Cash flow was a standout. Operating cash flow came in at $10.9 million, up 60% from $6.8 million in the year-ago quarter, while free cash flow (after $2.4 million in capex) hit $8.5 million. The company ended Q1 with $56.6 million in cash, up from $46.9 million at year-end, and remained debt-light with no revolver draw and minimal long-term obligations.
Guidance is light on precision, but management reaffirmed strong momentum and stated that Q2 would show continued growth in both AI services and Agility subscriptions. Analysts are expecting Q2 revenue near $61 million and EPS of $0.25-0.28, implying another sequential step-up. This is supported by a string of new customer wins in AI data engineering and multimillion-dollar expansions with existing top-tier tech clients – especially in the DDS segment, which accounted for $50.8 million, or 87% of total revenue, in Q1.
Customer concentration remains high – one DDS customer accounted for 61% of total revenue this quarter, up from 24% a year ago – but the sharp increase reflects the deepening of strategic engagements rather than dependency alone. While concentration risk exists, it also signals Innodata’s ability to scale within complex, long-term relationships.
With operating leverage improving, customer contracts scaling, and a strong cash position, INOD has crossed the profitability threshold – and is positioned to stay there. Management is guiding to full-year revenue growth of at least 40%, with momentum continuing across AI data services and recurring subscription platforms. That puts Innodata on a path not just to scale, but to do so with margin expansion and disciplined execution.
Source: Innodata Q1 2025 Investor Presentation
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Beta with a Backbone
Innodata’s stock has gained over 244% in the past 12 months, though it clearly still has room to run. Like many AI-related names, INOD surged from late 2024 into February 2025 before a steep pullback amid tariff-driven risk-off sentiment. The stock fell more than 50% from its all-time high, but then rallied over 54% from its April 4 low – classic high-beta behavior. That volatility fits INOD’s profile: it trades with a beta of approximately 2.6 and a market cap of just $1.4 billion, making sharp swings par for the course.
Amid that roller-coaster ride, analysts remain bullish, rating INOD a “Strong Buy” with average price targets implying ~50% upside over the next 12 months. Wall Street appears to expect Innodata’s inherent volatility to trace a strongly rising regression line. That optimism was reinforced when Wedbush named Innodata one of “30 companies defining the future of AI,” alongside heavyweights like Nvidia, Google, Palantir, and TSMC.
Though Innodata operates like a growth tech company, it’s classified in the Industrials sector under GICS – reflecting its legacy work in data prep and outsourcing. That classification could change, but for now it skews valuation comparisons: INOD looks expensive next to industrials but offers superior fundamentals compared to tech peers.
When benchmarked against industrial services, INOD’s P/E, EV/Sales, and EV/EBITDA ratios appear stretched – but compared to small-cap AI/data infrastructure and high-growth SaaS firms, its valuation is on par or lower. Its GAAP PEG ratio sits at 0.03, which looks absurdly low given its ultra-fast growth. INOD also delivers strong financial quality: ROE, ROA, and return on total capital (ROTC) outperform comparable firms – including the undisputed leader Palantir. That checks both the growth and quality boxes – not just hype.
This confirms the potential Wall Street sees in the stock – and possibly more. While INOD’s stock has already run hard, the real opportunity lies in re-rating – as markets begin to price in sustained profitability, platform monetization, margin leverage, and a meaningful share of AI infrastructure spending. The INOD narrative is shifting from “high-beta moonshot” to “profitable back-end enabler with real optionality.”
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To Sum It All Up
Innodata is a data engineering and AI-enablement platform powering some of the most complex and sensitive workflows behind generative AI. Operating at the convergence of data curation, model fine-tuning, and platform-based delivery, Innodata embeds itself within the pipelines of leading AI labs and enterprise users. Its combination of human-in-the-loop tooling, domain-specific structuring, and managed service deployment enables it to meet the scale, precision, and compliance demands of frontier AI development. With growing platform adoption, expanding use cases across healthcare and finance, and a deepening role in AI infrastructure, Innodata is evolving from a data prep vendor into a strategic layer for intelligent systems. For investors seeking high-growth exposure to the operational backbone of AI, Innodata offers a volatile but increasingly credible bet on the picks-and-shovels side of the AI revolution.
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Smart Growth Portfolio
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Click here for more stock analysis from TipRanks Macro & Markets research analyst Yulia Vaiman
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Disclaimer
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