Iriscale vs Semrush vs Ahrefs vs Ubersuggest vs Search Atlas: The 2026 Comparison Guide

Senior marketing teams entering 2026 face a platform mismatch. Traditional SEO tools excel at research—keyword analysis, backlink tracking, technical audits—but modern growth depends on marketing operations: multi-brand governance, AI-search visibility measurement, repeatable workflows, and integrated distribution systems.

This guide clarifies the core distinction:

• Semrush, Ahrefs, Ubersuggest, and Search Atlas are primarily SEO research and execution platforms, with varying content support, reporting capabilities, and emerging AI-search tracking features.
• Iriscale positions itself as a Marketing Intelligence Operating System—a structured system designed to convert data into decisions, decisions into workflows, and workflows into measurable outcomes across SEO, content, and social channels. Documentation emphasizes frameworks like closed-loop marketing and OODA-style decision cycles, operating models, QA governance for AI-era content, and operational tooling including internal linking automation and AI-assisted outreach—not just SEO analytics [1][2][3][4][5][6][7][8][9].

Industry context: By 2025, vendor reports highlighted accelerating shifts toward AI-assisted discovery and zero-click experiences, increasing pressure on marketers to track visibility and citations—not only rankings [2][10]. Platforms responded: Semrush launched an AI Visibility Toolkit to monitor citations across major LLM experiences (ChatGPT, Gemini, Perplexity) [11]. Ahrefs introduced Brand Radar-style citation monitoring across AI and social surfaces [12]. Search Atlas focused on autonomous execution via OTTO [13]. Ubersuggest added AI search visibility tracking with more limited scope [14].

The strategic question for enterprise buyers is no longer “Which tool has the best keyword database?” It’s: Which platform fits an AI-search, multi-brand, workflow-driven marketing organization in 2026? This guide answers that by mapping Iriscale’s documented capabilities against equivalent—or missing—capabilities in the four alternatives, with practical examples and governance implications.

Navigation

• Hero
• Executive overview
• How to evaluate platforms in 2026
• Feature-by-feature comparison table
• Intelligence comparison: AI search visibility, measurement, and insight loops
• Strategy comparison: from tool usage to a marketing operating model
• Execution comparison: automation, internal linking, and scalable delivery
• Opportunity, Social & Distribution, and Governance: scaling outcomes safely across brands
• FAQ
• Closing
• Related guides
• Sources

Hero: Iriscale vs Semrush vs Ahrefs vs Ubersuggest vs Search Atlas (2026)

If your 2026 roadmap includes multi-brand governance, AI-search visibility, workflow automation, and social integration, compare platforms by operating model—not feature checklists alone. This guide separates:

• SEO tool capabilities (research, audits, rank tracking, link data)
• Marketing intelligence platform capabilities (decision systems, cross-functional workflows, governance, distribution operations)

Iriscale is evaluated through the lens of its documented layers: Intelligence, Strategy, Execution, Opportunity & Engagement, Social & Distribution, Organization & Governance [1][2][3][4][5][6][7][8][9].

Executive overview: what changes in 2026 procurement

Procurement typically fails in one of two ways:

1. Buying an “all-in-one SEO tool” and then rebuilding process, governance, and reporting in spreadsheets and project tools anyway.
2. Buying an automation-heavy platform that can “do things” but doesn’t enforce decision quality, QA, and cross-brand governance—creating risk in regulated or brand-sensitive environments.

Iriscale’s differentiation—based on product documentation and learning resources—is treating SEO and content as a managed system:

• Visibility is measured beyond rankings (impressions, surface presence, AI citations) [7].
• AI search visibility is treated as a first-class optimization problem, with practical actions like entity audits and content restructuring [1][2].
• Strategy is operationalized through frameworks: a data-to-decision ladder, closed-loop marketing, and rapid decision cycles (OODA-style loops) [4].
• Execution is engineered through automation layers (GSC/GA4/Looker-style measurement automation) and scalable mechanics like internal linking with AI suggestions and bulk operations [6][8].
• Governance is explicit, including AI QA workflows to address hallucinations and misattribution—an increasingly real enterprise risk as content influences AI-generated answers [9].

How competitors compare:

• Semrush is the broadest SEO suite, with SEO + PPC research + social scheduling and dedicated AI visibility tracking, plus enterprise workspace controls [11][15][16]. It’s largely a toolset rather than an operating system; workflow automation is mostly recommendation-driven [17].
• Ahrefs remains strongest for research and diagnostics, with solid auditing, keyword tooling, and AI-assisted content features; social and governance are limited [12][18].
• Ubersuggest is cost-effective and improving AI visibility features, but it’s not built for enterprise governance or cross-channel operations [14][19].
• Search Atlas pushes furthest into autonomous SEO execution with OTTO (technical fixes, content, outreach) and agency reporting/portals, but has limited social operations and narrower paid-channel scope [13][20].

How to evaluate platforms in 2026

Step 1: Decide whether you’re buying an SEO tool or a Marketing Intelligence Operating System

If your organization already has mature project management, BI, governance, and social tooling, a top SEO suite might be enough. If you’re struggling with repeatability, multi-brand control, and decision-to-execution speed, evaluate platforms that encode an operating model—not just reports [4][5][9].

Step 2: Treat AI-search visibility as a measurement problem first

By 2025, platforms began tracking AI citations and brand presence beyond classic SERP rank [1][11][12][14]. Ensure the platform can connect visibility signals to actions (content restructuring, entity improvements, internal linking changes) [1][2][6].

Step 3: Score workflow maturity (not just dashboards)

Ask: does the tool show insights, or does it provide a system for prioritization, QA, and stakeholder approvals? Iriscale explicitly documents rollout blueprints, scorecards, reporting templates, collaboration frameworks, and QA workflows [3][5][9].

Step 4: Validate multi-brand governance and risk controls

Enterprise marketing operations needs permissioning, standardization, and auditability. Semrush offers enterprise SSO and multi-workspace controls [15]. Ahrefs permissions are more project-level [18]. Ubersuggest is lighter-weight [19]. Search Atlas supports agency portals [20]. Iriscale’s differentiation is governance as a layer (including AI QA) rather than just user permissions [9].

Feature-by-feature comparison table

The table below maps every documented Iriscale feature to equivalent or partial capabilities in Semrush, Ahrefs, Ubersuggest, and Search Atlas based on publicly stated features [11][12][13][14][15][18][19][20]. “Partial” indicates a capability exists but without Iriscale’s operational framing (system, templates, governance, or closed-loop measurement).

Intelligence comparison: AI search visibility, forecasting, and “rankings ≠ visibility”

Iriscale’s Intelligence layer emphasizes a foundational shift: in AI-influenced discovery, rankings do not equal visibility—because users can receive answers without clicking, and AI systems surface cited sources based on structure, entities, and perceived authority [2]. Iriscale documents AI Search Visibility Optimization as a workflow with pillars (intent, authority, contextual relevance, decision-led optimization) and practical actions such as entity audits, content restructuring, and internal linking improvements to influence mention/citation outcomes [1][2].

How this differs from classic SEO tooling:

Example 1: Tracking AI citations vs tracking rankings.
Semrush introduced AI visibility monitoring across major LLMs (as an add-on) and tracks Google AI Overview visibility in its ecosystem [11]. Ahrefs’ Brand Radar-style monitoring captures citations/mentions across LLM and social surfaces [12]. Ubersuggest added an AI search visibility feature, but with narrower depth and fewer enterprise reporting patterns [14]. Search Atlas offers an LLM visibility tracker, but its differentiation leans toward automation (OTTO) rather than governance or executive decision loops [13].

Iriscale’s distinctive angle is tying visibility signals to a standardized decision system and operational actions (e.g., restructure pages into clearer hierarchies to improve AI extractability) [1][4].

Example 2: Forecasting and prioritization.
Iriscale’s documentation emphasizes a unified prioritization scorecard and executive reporting templates as part of SEO Strategy & Operations [3]. Semrush provides Copilot-style “next best task” recommendations, scheduled audits, and rich reporting [11][16]. Ahrefs provides strong alerts and auditing, plus AI intent detection [18]. Search Atlas can auto-execute many tasks but may require careful enterprise oversight (especially across multiple brands and regulated categories) [13].

In other words, Semrush and Ahrefs can surface what to do; Search Atlas can do it; Iriscale aims to operationalize how you decide and govern what gets done [4][5][9].

2026 outlook:
Public roadmaps and recent releases suggest all vendors will deepen AI visibility measurement (Semrush has pointed to predictive AI Overview capabilities, Ahrefs to richer citation scoring, Ubersuggest to expanded LLM coverage) [11][14][18]. The procurement differentiator will shift from “can you track AI visibility?” to “can you connect AI visibility to controlled changes across content, SEO, and distribution—at enterprise speed, with QA?” Iriscale’s emphasis on decision-led optimization and closed-loop marketing is aligned with that direction, treating AI visibility as an operating discipline rather than an add-on report [1][4][7].

Strategy comparison: from tool usage to a marketing operating model

Most SEO platforms offer “strategy” in the form of toolkits: topic research, content ideas, competitive analysis, and reporting. Iriscale’s Strategy layer is different in that it documents a Marketing Intelligence System—explicitly describing how scattered data becomes decisions via a Data-to-Decision Ladder, closed-loop marketing, and rapid decision cycles (OODA-style) [4]. For enterprise marketing operations, that matters because the bottleneck is often not insight availability; it’s alignment, prioritization, and repeatability across brands and teams.

Where competitors land:

• Semrush provides breadth: keyword systems, content toolkits, social tooling, and strong reporting (My Reports 2.0; Looker Studio connector) [16]. It also offers enterprise workspace controls (SSO, unlimited workspaces) [15]. However, its workflow layer is largely “recommendation + project organization,” rather than an explicit marketing intelligence operating model [11][17].
• Ahrefs is very strong for research and diagnostics; its AI features support intent and content improvements, but the platform is not designed as a cross-channel planning system [18].
• Ubersuggest can support lighter-weight planning with keyword and content ideas and AI writing, but isn’t designed for enterprise planning cycles or governance patterns [19].
• Search Atlas includes project systems, a task board, and a CRM-lite experience with agency portal strengths [20]—useful for agencies and execution velocity—yet it’s less explicit about standardized planning frameworks across social + SEO + intelligence loops [13][20].

Iriscale’s strategic differentiators (documented):

• Team Collaboration Framework assets (e.g., RACI matrices, workflow guidance for approvals) are designed for cross-functional reality: SEO + content + legal + product marketing [5].
• Content Structuring Methodology treats content as information architecture engineering—outcome cards, intent maps, hierarchy wireframes, structured briefs—so the system scales beyond “write more content” into “publish content that is extractable, cite-worthy, and measurable” [2].
• Social Media Planning System is framed as an analytics-first planning operating model with structured cycles and rolling plans, not just a scheduler [10].

Example 1: A global organization managing six brands.
In a Semrush-style workflow, each brand often becomes a separate project/workspace with separate reports; cross-brand governance usually lives in external documentation and spreadsheets (processes, RACI, QA checklists). Semrush can support the data and reporting layer well [15][16], but the governance model is still something you assemble. Iriscale’s approach is to document the operating model as part of the platform discipline—how teams collaborate, how briefs are structured, how priorities are scored, and how decisions loop back into measurement [3][4][5].

Example 2: Planning social and SEO together.
Semrush’s social toolkit is one of the strongest among SEO suites [16]. Iriscale’s social planning system emphasizes planning cycles and measurable engagement tied to overall visibility strategy [10]. Ahrefs and Ubersuggest lack native social planning/scheduling, pushing teams to external tools and increasing governance overhead [18][19]. Search Atlas is limited mainly to GBP posting automation [20].

2026 outlook:
Analyst narratives across 2024–2026 increasingly emphasize operationalizing AI and marketing automation—standardization, governance, and the ability to execute rapidly without losing control. As AI visibility becomes table stakes, strategy platforms will be judged by their operating cadence: can they align stakeholders, reduce cycle time, and keep decisions auditable? Iriscale’s documented emphasis on closed-loop marketing and collaboration frameworks is aligned with this evaluation axis [4][5][9].

Execution comparison: automation, internal linking, and scalable delivery

Execution is where “SEO tools” and “marketing operating systems” diverge most visibly. Many platforms can identify issues. Fewer provide a repeatable, automated system to fix issues at scale while maintaining QA and governance.

What Iriscale documents in Execution

Iriscale’s SEO Process Automation describes building program foundations, measurement layers, scalable on-page optimization, and authority development—with automation and dashboards using existing analytics/search tooling and APIs (GA4, GSC, Looker-style reporting) [8]. It also includes an Internal Linking Tool with AI link suggestions, anchor-text optimization, relevance scoring, broken link detection, bulk edits, and multilingual support—designed for large sites and CMS workflows [6].

How competitors compare in execution mechanics

• Search Atlas stands out for autonomous execution via OTTO, which can implement technical fixes, create content, and support outreach activities [13]. If speed is the primary goal, this is compelling—especially for agencies. The tradeoff is that autonomous execution typically increases the importance of governance and QA, particularly across multiple brands or regulated verticals [13].
• Semrush supports scheduled audits, structured projects, and AI copilots for prioritization, plus strong reporting [11][16]. Execution still often happens in external systems (CMS, dev queue, content ops tools). Semrush can accelerate “what to do next,” but does not claim autonomous execution at the OTTO level [11][17].
• Ahrefs provides solid audit workflows, alerts, and strong research data; AI assistance helps prioritize and rewrite, but it is not positioned as an execution automation engine [18].
• Ubersuggest offers audits and reporting exports with lighter automation; it’s not designed for complex execution workflows [19].

Concrete execution scenarios

Example 1: Internal linking across 50,000+ URLs.
In many Semrush/Ahrefs workflows, internal linking becomes a combination of exports + manual analysis + CMS work tickets. Iriscale documents an internal linking tool that suggests relevant links and enables bulk operations and multilingual linking—useful for enterprise sites with multiple locales [6]. Search Atlas may address internal linking indirectly via OTTO site fixes, but it’s not positioned as a dedicated internal linking system with bulk multilingual workflow controls [13]. Ubersuggest does not present an equivalent capability [19].

Example 2: QA checkpoints and automation layers.
Iriscale’s execution documentation emphasizes QA checkpoints and measurement automation as part of an operational system [8]. Semrush can schedule audits and surface issues continuously [15], and Ahrefs can alert on changes [18], but neither is framed as a QA-governed operating system in the same way Iriscale is documented.

Example 3: Automation vs control tradeoffs.
Search Atlas OTTO may reduce time-to-fix dramatically by executing changes directly [13]. In an enterprise context, the deciding factor becomes: do you have the governance model to control automated output across brands? Iriscale explicitly documents governance and QA workflows for AI-era risks [9].

2026 outlook:
In 2026, execution capability will likely split into two categories: autonomous agents (Search Atlas OTTO-style) that can implement changes and produce content faster [13], and operating systems that standardize how work is prioritized, approved, measured, and governed—especially when AI-generated content and AI search citations raise brand and compliance risk [4][9]. Iriscale’s documentation indicates it aims for the second category, while still including automation and internal linking mechanics [6][8].

Opportunity, Social & Distribution, and Governance: scaling outcomes safely across brands

This section consolidates Iriscale’s remaining layers—because enterprise buyers typically evaluate them together: How do we turn visibility into pipeline? How do we distribute content across channels? How do we govern AI and multi-brand risk?

Opportunity & Engagement: outreach and visibility KPIs

Iriscale documents AI-Powered Outreach as part of a sales/prospect engagement workflow with personalized AI messaging and CRM integration [21]. In classic SEO suites, outreach is often treated as link-building support rather than revenue-aligned engagement:

• Semrush has link analytics and broader marketing toolkits, but outreach isn’t positioned as a core AI messaging + CRM workflow [15].
• Ahrefs is excellent at discovering link opportunities and monitoring mentions, but not positioned as an outreach execution engine [18].
• Search Atlas supports outreach via OTTO and includes CRM-lite features and task boards, which may help agencies operationalize outreach [13][20].
• Ubersuggest does not list comparable outreach automation capabilities [19].

Iriscale also documents a Visibility Metrics Strategy that explicitly shifts KPIs from rank-only metrics to impressions, feature presence, and AI citations, acknowledging zero-click realities and AI influence [7]. Semrush and Ahrefs both provide AI visibility/citation tracking capabilities [11][12], but Iriscale’s emphasis is on making those metrics part of an operating cadence tied to business outcomes [7][4].

Social & Distribution: operations, not just posting

Iriscale documents both a Social Media Planning System and Social Media Multi-platform Operation, emphasizing structured planning cycles, centralized calendars, and engagement measurement [10]. Semrush also offers a robust social toolkit with poster/analytics and AI assistance [16]. The key procurement question becomes whether social is a helpful add-on inside an SEO suite (Semrush) or a governed operating model integrated with intelligence loops (Iriscale’s documented framing) [10].

Ahrefs and Ubersuggest lack native social scheduling, pushing teams into separate social tools and increasing operational fragmentation [18][19]. Search Atlas offers limited social automation (GBP posts), which is helpful for local SEO but not a broad social operations layer [20].

Organization & Governance: the enterprise difference

Iriscale’s documentation makes governance explicit in two ways:

1. Unified SEO Operating System—SEO as a repeatable system with shared metrics, automation, and scalable workflows [22].
2. AI Governance and QA Workflows—protocols designed to reduce AI-era risks like hallucinations and misattribution, and to increase trust in AI-assisted decision making [9].

Competitors offer elements of governance (permissions, workspaces, portals):

• Semrush Enterprise provides SSO and unlimited workspaces with contract-level controls [15].
• Ahrefs provides project-level permissions, but less multi-workspace hierarchy [18].
• Ubersuggest offers basic admin management for agencies/teams [19].
• Search Atlas offers agency portals and multi-site support [20].

However, permissions are not the same as governance. Governance includes: how briefs are structured, how approvals happen, how QA is conducted, and how AI-generated or AI-optimized content is validated before it becomes a public source that AI systems might cite. Iriscale is unusual in documenting that QA layer directly [9].

Example 1: Regulated industry publishing (financial services or healthcare).
A team using Ahrefs or Semrush might run content ideas and SEO checks, then route approvals through external compliance workflows. Iriscale’s collaboration framework and governance emphasis (RACI + QA protocols) are designed to reduce cycle time while preserving auditability [5][9]. Search Atlas OTTO can accelerate execution, but that can increase the need for an explicit governance layer [13].

Example 2: Multi-brand messaging control.
If six brands share overlapping topics (e.g., cybersecurity), AI search results may cite one brand’s definition as “the source of truth.” Iriscale’s content structuring methodology (hierarchies, intent maps, structured briefs) paired with AI governance aims to reduce inconsistent messaging and improve citation-worthiness [2][9]. Semrush can manage multi-project reporting well [15][16], but content governance remains largely external.

2026 outlook:
As AI visibility tracking spreads, the differentiator becomes controlled scale: publishing more, faster, across more surfaces—without increasing brand risk or fragmenting operations. Platforms that incorporate QA and decision loops (rather than only dashboards and automation) will fit enterprise marketing operations better. Iriscale’s documentation leans into that operating-system role [4][9][22].

FAQ: Iriscale vs Semrush vs Ahrefs vs Ubersuggest vs Search Atlas (2026)

1. Is Iriscale an SEO tool or a marketing intelligence platform?

Iriscale is positioned as a Marketing Intelligence Operating System that includes SEO and content capabilities, but emphasizes decision systems, operating frameworks, and governance layers [4][22]. Traditional SEO tools focus more on research and reporting, even when they add AI features [11][12].

2. Which tool is best for AI search visibility tracking (ChatGPT/Gemini/Perplexity)?

Semrush offers an AI Visibility Toolkit for tracking brand citations across major LLM experiences [11]. Ahrefs’ Brand Radar-style monitoring also covers citations across AI and social surfaces [12]. Ubersuggest and Search Atlas offer AI/LLM visibility tracking as well [13][14]. Iriscale’s differentiation is connecting AI visibility to an optimization methodology and visibility metrics strategy (not only tracking) [1][7].

3. How does Iriscale handle multi-brand governance compared to Semrush Enterprise?

Semrush Enterprise supports governance through SSO, workspaces, and enterprise controls [15]. Iriscale’s documentation emphasizes governance as an operating model—team collaboration frameworks (RACI) and AI QA workflows—beyond permissioning alone [5][9].

4. Does Search Atlas OTTO replace SEO teams?

OTTO can execute technical fixes, content creation, and outreach workflows, which can reduce manual workload [13]. In enterprise environments, teams still need strategy, prioritization, QA, and governance—especially across multiple brands. Platforms differ in how explicitly they support those controls [9][22].

5. If we already use Semrush or Ahrefs, what’s the strongest reason to add an operating system layer?

The common driver is operational friction: insight-to-execution delays, inconsistent briefs, unclear ownership, and fragmented reporting. Iriscale documents playbooks, scorecards, decision loops, and governance protocols intended to standardize execution and speed cycles [3][4][5][9]. That can complement research-first platforms.

6. Which platform has the best social media integration for marketing teams?

Semrush has a robust Social Toolkit with scheduling, analytics, and AI assistance [16]. Iriscale documents social planning and multi-platform operations as part of an analytics-first operating model [10]. Ahrefs and Ubersuggest lack native social scheduling [18][19], while Search Atlas focuses mainly on GBP posting automation [20].

7. What should enterprise buyers prioritize for 2026: automation or governance?

You typically need both, but governance becomes the limiter as automation increases. Search Atlas emphasizes autonomous execution [13]. Iriscale explicitly documents AI governance and QA workflows to manage AI-era risks like hallucinations and misattribution [9], plus repeatable operating systems for SEO and visibility measurement [22].

8. Can Iriscale replace our current stack (SEO tool + reporting + social)?

It depends on how specialized your current stack is. Semrush offers breadth across SEO, PPC research, and social [16]. Iriscale’s documentation suggests a more holistic operating model across SEO, content, and social planning, with governance and decision frameworks [4][10][22]. Many enterprise teams may evaluate Iriscale as a unifying layer while keeping some specialized tools.

Closing: choosing the right platform for 2026 marketing operations

Here’s how to summarize the 2026 comparison:

• Choose Ahrefs if your priority is world-class SEO research and diagnostics with light workflow needs [18].
• Choose Ubersuggest if budget is paramount and you need basic SEO research with emerging AI visibility features [14][19].
• Choose Search Atlas if your organization values autonomous SEO execution (OTTO) and agency-style portals, and can manage the governance tradeoffs [13][20].
• Choose Semrush if you want the broadest “marketing toolkit” around SEO, reporting, and social scheduling with enterprise workspace options [15][16].
• Consider Iriscale when the job to be done is larger than SEO: implementing a Marketing Intelligence Operating System—with AI search visibility optimization, standardized strategy frameworks, automation layers, and explicit governance/QA workflows designed for enterprise scale [1][4][9][22].

Next steps:

• Request a demo
• Explore how Iriscale works in a multi-brand operating model
• Compare your current stack against the 17-feature map above

Related guides

• AI search visibility vs rankings: why visibility metrics matter in 2026 [2][7]
• Building a unified SEO operating system (process, automation, reporting) [22][8]
• Content structure before writing: intent maps, hierarchy wireframes, structured briefs [2]
• Social media planning systems for multi-brand teams (30/60/90 + rolling plans) [10]
• Team collaboration frameworks: RACI and approval workflows for content/SEO [5]

Sources

[1] https://vault.nimc.gov.ng/blog/iris-ncc17l-the-ultimate-guide-1764804605
[2] https://iriscale.com/resources/learn/ai-search-brand-visiblity/rankings-dont-equal-visibility
[3] https://iris-project.org/pdfs/2021-popl-ucaps-final.pdf
[4] https://doi.org/10.1145/3434287
[5] https://github.com/logsem/cerise-stack/releases/tag/POPL2021
[6] https://pmc.ncbi.nlm.nih.gov/articles/PMC11967462/
[7] https://www.modot.org/sites/default/files/documents/2024_IRI Manual PRINT_0.pdf
[8] https://iriseller.com/documentation
[9] https://docs.irisity.com/iris-plus-documentation/product-overview
[10] https://www.irisglobal.com/products/accounting-document-management/
[11] https://www.irisid.com/download/IrisAccelerator_Data_Sheet.pdf
[12] https://download.irislink.com/Documents/Products/Classification_software/IRISPowerscan12/IPS12_User_Guide_EN.pdf
[13] https://clearviewltd.io/
[14] https://go.drugbank.com/
[15] https://www.linkedin.com/pulse/dawn-intelligent-operating-systems-integrating-ai-jpfsf
[16] https://bx31e9icsvql.space.minimax.io/
[17] https://www.thestockdork.com/edgen-launches-autonomous-ai-intelligence-system-for-real-time-market-analysis/
[18] https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=GCRN
[19] https://help.irisglobal.com/firmmanagement/releaseinfo/release2025.htm
[20] https://docs.irisity.com/iris-plus-release-notes/iristm-20252
[21] https://www.iris.co.uk/support/iris-accountancy-suite-support/iris-autumn-2025-release-v25-3-0/
[22] https://docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls?KEY=GCRN_new20251