RSSS

• Overall Financial Results

  • Total Q2 FY26 revenue was $11.8 million, flat compared to $11.9 million in Q2 FY25. Gross profit rose 6% year-over-year to $6.2 million, with gross margin improving 350 basis points to 52.4%, driven by a mix shift to higher-margin platform revenue (which now represents 44% of total revenue, up from 39% year-over-year).
  • Net income was $547,000 ($0.02 per diluted share), compared to a net loss of $2 million ($0.07 per diluted share) in the prior year quarter (which included a $2.4 million contingent earn-out charge). Adjusted EBITDA was $1.3 million, up 36% year-over-year, with a 12-month trailing adjusted EBITDA margin of 11.8%.
  • Cash and cash equivalents totaled $12.3 million at quarter-end, with operating cash flow of $1.4 million, up 35% year-over-year. The company has no outstanding borrowings on its line of credit and has funded all Site earn-out obligations to date from operating cash flow.

• Strategic Product Shifts

  • The company is shifting from selling seat-based platform subscriptions to selling API infrastructure embedded in customers' internal systems and AI tools. These API deals are 2x to 5x larger than traditional seat contracts, have lower churn, and are more mission-critical for customers. Multiple large enterprises already use the company's API to power internal AI research tools, with one large pharma customer making over 1 million annual API calls, and publishers are in active discussions to use the company's infrastructure for AI-enabled customer access.
  • The company is evolving from a pure document delivery business to an answers-and-access platform: it now helps researchers answer research questions first (via CITE for citation verification and claim validation) before delivering full copyrighted articles through Article Galaxy, creating a more complete end-to-end solution. This shift has driven expanded enterprise and academic deployment of the company's full product suite.
  • The company has integrated with leading LLMs (including Claude and ChatGPT) to deliver copyright-compliant, fully cited research answers directly within AI tools, leveraging its unique access to paywalled content, entitlement management, and rights management capabilities that generic LLMs do not have.

• Operational Efficiency

  • Management has maintained strict discipline on general and administrative (G&A) costs, with total Q2 operating expenses declining to $5.4 million from $5.7 million in the prior year quarter. Lower G&A and stock-based compensation offset increased sales and marketing investment. The company is running a cross-vendor cost savings program to eliminate redundant expenses.
  • Internal use of AI tools has dramatically improved productivity across product development, data analysis, and back-office functions, allowing the company to ship product improvements (including new patent data and software updates) faster than ever before.

• Management expects the seasonality trend of stronger performance in the second half of the fiscal year to hold, with Q3 and Q4 typically the company's strongest quarters for adjusted EBITDA.
• Management expects year-over-year transaction revenue declines to continue in the second half, driven by the previously announced churn of one large account, even as sequential transaction revenue will be higher than the first half. Excluding the churned account, transaction performance is expected to stay within normal seasonal ranges.
• B2C competitive headwinds are expected to continue through the second half, as increased competition for digital marketing keywords keeps trial-to-subscriber conversion below prior year levels.
• The company's objective is to exceed fiscal 2025 adjusted EBITDA levels in each of the remaining two quarters of FY26, grow operating cash flow, and exit the year with a stronger earnings and cash generation run rate while maintaining a flexible balance sheet.
• Management targets returning the company's overall SaaS ARR growth rate to 20%+ over time, leveraging the larger, higher-margin API and AI infrastructure opportunity.

1. B2B Segment: Total B2B annual recurring revenue (ARR) was $15.3 million, contributing 70.2% of the company's total ending ARR. The segment added 47 net new platform deployments, grew platform subscription revenue 14% year-over-year to $5.2 million, and delivered 6% quarter-over-quarter ASP growth. Total incremental ARR for the quarter was a company record $560,000 for an organic second quarter, with total ending company ARR up 14% year-over-year to $21.8 million. The platform business (predominantly B2B) recorded a gross margin of 88.1%, a 160 basis point year-over-year increase.

2. B2C Segment: Normalized B2C ARR was $6.4 million, contributing 29.8% of total ending ARR. The segment saw soft ARR results driven by increased competition for digital marketing keywords and lower trial-to-subscriber conversion rates. Management intentionally pulled back spending on underperforming marketing channels to prioritize cohort quality and long-term retention over short-term growth. B2C churn has declined year-over-year, a trend that has continued into Q3 FY26.

3. Transaction Segment: Transaction revenue was $6.6 million, down 9.6% year-over-year from $7.3 million. The decline is almost entirely attributable to one churned large account and volume reductions from a small number of other large customers; excluding these factors, transaction revenue was down ~2% year-over-year, within normal seasonal ranges. Gross margin for the transaction business was 24%, down 120 basis points year-over-year, due to lower fixed cost leverage from reduced revenue and copyright margin pressure.

• Increased competition in the B2C segment has pushed up digital marketing costs and lowered trial-to-subscriber conversion rates, creating ongoing headwinds for short-term B2C growth.
• General AI disruption of enterprise research software has created broad market stock price volatility, and generic LLMs or large publishers could develop competing capabilities that would pressure the company's market position.
• The new API/AI infrastructure business model is still evolving, including pricing structures and revenue sharing with publishers, so long-term revenue and margin trajectories for this segment are not yet fully defined.
• Transaction revenue is exposed to variability in corporate research intensity that is outside the company's control, and large customer churn or volume cuts can create material year-over-year revenue declines.

Q: Given the strong B2B results, how is the B2B pipeline evolving, especially for the new API/AI model? And are there early signs of B2C returning to growth in H2?

A: The B2B pipeline has grown consistently quarter-over-quarter and year-over-year, with a large share of the current pipeline consisting of larger API/AI integration deals, which are much larger in value than traditional seat contracts. For B2C, competition for digital marketing keywords has increased dramatically, and while trial volume remains similar to a year ago, trial-to-subscriber conversion is lower. The product team is adding new features like patent data to improve conversion, and churn has improved year-over-year with the trend continuing into Q3, but management cannot confirm a return to growth in H2. B2C2B (where individual B2C users convert their organization to enterprise contracts) is a growing secondary benefit of the B2C business.\n\nQ: How are you leveraging AI internally for cost savings and productivity, and what is the size of the market opportunity for your new API infrastructure model?

A: The company is already fully leveraging AI across the organization, most notably to dramatically speed up product development and improve productivity for software engineers, data analysts, and back-office teams. AI is currently a productivity multiplier, not a major headcount cost reduction, though it enables the team to deliver more product improvements with existing staff. The company serves the same core vertical markets as before, but API deals have ASPs that are 20-30% higher than traditional contracts, and usage-based pricing for API calls will allow revenue to scale with increased AI tool usage. The pricing model for API and AI infrastructure will continue to develop over the next 12 months, with early traction showing shorter, more straightforward sales cycles than traditional seat deals.\n\nQ: Is the expected H2 transaction revenue decline year-over-year driven entirely by the previously announced large customer churn, or are there new customer pullbacks?

A: The expected year-over-year decline is almost entirely from the already announced churned large account. Transaction volumes will still increase sequentially in H2 (following normal seasonality) compared to H1, but will remain down year-over-year due to the lost churned account. Excluding the churned account, transaction revenue is down just 2% year-over-year, which is within normal variability tied to changes in customer research intensity, with no material new churn beyond the previously announced customer set.\n\nQ: Could large LLM providers or top publishers replicate your API/rights management capability, and how are relationships with the long tail of publishers evolving for AI infrastructure?

A: Large top publishers will likely develop their own AI connectors, but the long tail of small and medium publishers do not have the resources to build this capability, and customers do not want to manage hundreds of separate connectors to different publishers. The company has 10+ years of established relationships with the long tail of publishers, is already in active discussions to partner on AI rights management and infrastructure, and offers a no-upfront-cost solution for publishers to enable AI-compliant access to their content. This opportunity is still early with minimal current revenue impact, but early traction is encouraging, and API deals already have a floor price significantly higher than the company's average legacy contract. It also opens potential new revenue streams from publisher partnerships and new customer verticals like financial services.