CloudAiry AI pedigree vs Evagene: AI diagrammer or clinical tool?

Short version. CloudAiry is an AI-first diagramming product whose pedigree chart maker generates pedigrees from prompts, recognises inheritance patterns (autosomal dominant, autosomal recessive, X-linked recessive, mitochondrial), and exports PNG and PDF. Its target audience is biology students, teachers, medical students, genetics professionals, and researchers. It carries SOC 2 Type II, ISO 27001, and GDPR credentials, which is unusual for the education-diagramming category. Evagene is a clinical-grade pedigree management platform with standard notation enforcement, an ICD-10 and OMIM disease catalogue, BayesMendel cancer risk models, AI interpretation with bring-your-own-key (BYOK) LLMs, and a full API/MCP/embed surface for clinical integration. Of the generic-diagrammer comparisons on this site, CloudAiry overlaps most with Evagene on the AI axis — but the two products use AI for different jobs.

This is an honest comparison. CloudAiry is a capable AI diagramming tool with legitimate strengths in the education and professional-illustration segment. The aim here is to clarify where an AI diagramming tool reaches the edge of its remit and where a clinical-grade platform takes over. CloudAiry claims are drawn from its public AI pedigree chart maker page as of April 2026.

What's a clinical pedigree tool for, and where do generic diagrammers fit?

A pedigree chart at its simplest is a family picture — squares, circles, lines, shading. An AI diagram tool like CloudAiry is very good at producing that picture from a natural-language prompt, and at inferring visible properties of the family once the picture exists (which generation is which, what inheritance pattern the pattern of shaded individuals suggests, whether a condition might be mitochondrial). For education, illustration, and professional visual communication, this is a real convenience.

A clinical pedigree tool does something different. The diagram is a view over a structured clinical record. Each individual is an object with sex, date of birth, vital status, a list of diseases coded to ICD-10 and OMIM, relationships that the software understands biologically, and often additional clinical metadata (age at diagnosis, age at death, genotype, surveillance status). From that structured record, it offers capabilities that a diagrammer — even an AI-powered one — cannot: risk models (BRCAPRO, MMRpro, PancPRO) computing carrier probability and lifetime cancer risk; notation enforcement preventing inconsistent diagrams; disease ontologies making annotations machine-readable; batch risk screening across all catalogued conditions; clinical reporting formatted for the medical record; and interoperability via GEDCOM, FHIR, REST API, webhooks, and embeddable viewers.

The difference is not whether AI is involved. It is what the AI is being applied to. CloudAiry's AI draws and analyses the picture. Evagene's AI interprets the clinical record — the pedigree the clinician built, with structured disease codes, risk model outputs, and family-history dates — and drafts a narrative report clinicians can review. Both are legitimate uses of AI. They serve different workflows.

CloudAiry is clear about its positioning. Its target audience is educational and professional; its AI pedigree generator sits alongside AI family tree, flowchart, mind map, and block diagram tools. Clinical genetics is not the stated centre of gravity, though medical students and genetics professionals are in the target list. The product is honest that it is an AI diagramming suite, not a clinical platform.

How the two products position themselves

CloudAiry positions itself as an AI-assisted pedigree chart maker for education and professional use, with over fifty thousand users across biology students, teachers, genetics professionals, medical students, and researchers. Its public pedigree chart maker page highlights AI generation of standard symbols (squares, circles), automatic inheritance-pattern analysis (autosomal dominant, autosomal recessive, X-linked recessive, mitochondrial), multi-generation alignment, and PNG and PDF export. It integrates with other Cloudairy AI tools (family tree, flowchart, mind map, block diagram). Pricing is tiered: Free, Starter at four US dollars per member per month billed annually, Business at five US dollars per member per month billed annually, and Enterprise on custom terms. Security credentials include SOC 2 Type II, ISO 27001, and GDPR compliance.

Evagene positions itself as clinical-grade pedigree management for precision medicine. The pedigree is the central clinical artefact — drawn on a gesture canvas during consultation, annotated from a curated 200-plus disease catalogue coded to ICD-10 and OMIM, analysed by integrated BayesMendel risk models (BRCAPRO, MMRpro, PancPRO) and Mendelian inheritance calculators, interpreted by AI through your own LLM keys, and delivered as one of four clinical report types. Around that core sits a developer platform: a scoped REST API, HMAC-signed webhooks, an MCP server exposing 11 pedigree tools to AI agents, and an embeddable viewer for patient portals and EHR integration layers.

The category difference is about what the product is ultimately for. CloudAiry is an AI diagramming suite that includes a pedigree generator. Evagene is a clinical pedigree platform whose AI is one of several surfaces the clinical workflow depends on.

Feature-by-feature comparison

The matrix below compares publicly advertised capabilities. A tick means the feature is on the vendor's public page or documentation; a dash means it is not publicly listed. Omission does not imply impossibility, only that it is not advertised as a product feature.

Matrix compiled from publicly available product pages and documentation as of April 2026. "—" indicates the capability is not publicly advertised.

Pedigree drawing and symbol enforcement

CloudAiry's drawing experience is distinctive in this category because the AI does much of the work. Describe a family in a prompt ("a four-generation family with suspected autosomal dominant condition in the maternal line") and CloudAiry produces a reasonable pedigree with standard symbols, multi-generation alignment, and a plausible inheritance pattern. For education and illustration — slide figures, lab report drawings, tutorial examples — this is efficient and reduces the manual click-through other diagramming tools demand.

What CloudAiry does not appear to enforce on its public pedigree page is NSGC or ISCN notation as a structured rule set. The symbols are AI-generated standard shapes (squares, circles) rather than data-backed clinical objects with validated sex, affected status, carrier status, and relationship semantics. For an educational diagram this is immaterial. For a clinical record, the absence of enforcement means a generated diagram can look correct and still be inconsistent with its underlying meaning — especially important because AI-generated content is plausible by design, and a plausible-but-wrong pedigree in a clinical context is a hazard.

Evagene's approach is structural: individuals are data objects with sex, vital status, dates, affected-disease list, and relationships; the symbol rendering is derived. Where Evagene's AI comes in is interpretation of that structured record, not generation of the drawing. The user draws (or imports) the pedigree with whatever tool they have; the AI reads the structured data and drafts a narrative clinical report. That separation — AI applied to a validated record, not to the pixels — is deliberate.

AI for drawing vs AI for interpretation

This is the axis where CloudAiry and Evagene differ most interestingly, and it deserves its own section because both products use AI, but for different jobs.

CloudAiry's AI generates and analyses the diagram. From a prompt, it draws. From a drawn diagram, it infers inheritance pattern (autosomal dominant, autosomal recessive, X-linked recessive, mitochondrial). It aligns generations, places symbols, and produces a visually coherent pedigree. This is valuable for users whose bottleneck is drawing the picture in the first place — students learning genetics, teachers preparing material, researchers producing figures.

Evagene's AI interprets the clinical record. Once the pedigree exists (drawn by gesture canvas, imported from GEDCOM, imported from an image via OCR, imported from 23andMe), Evagene's AI reads the structured data — individuals, sex, dates, ICD-10 / OMIM disease codes, risk model outputs — and produces a narrative clinical report covering key findings, family implications, data gaps, and screening recommendations. The user brings their own LLM keys (Anthropic Claude, OpenAI GPT), so inference traffic goes directly to the model account the service has already risk-assessed and contracted with. No Evagene-hosted model sits between the clinician and the LLM.

On top of interpretation, Evagene offers Analysis Templates — custom AI prompt templates with variable injection that let a service codify its house style of report writing and reuse it across cases — and an MCP server exposing 11 pedigree tools to Claude Desktop, Claude Code, and any MCP-compatible AI agent, so a clinician can ask their AI assistant to read, modify, or analyse a pedigree directly from inside their normal AI workspace.

Both approaches are legitimate. If your bottleneck is drawing the pedigree, CloudAiry's AI is well-aimed. If your bottleneck is interpreting a drawn pedigree in a clinical context — producing a narrative report, stratifying cancer risk, flagging testing eligibility — Evagene's AI is in a different class of job, and has to be grounded in a structured clinical record that a diagramming tool alone does not provide.

Clinical features that don't exist in an AI diagramming tool

Beyond AI surface, several capabilities are outside CloudAiry's remit and cannot be added without a clinical data model:

• Hereditary cancer risk models. BRCAPRO, MMRpro, and PancPRO are Bayesian models requiring structured family data — ages, affected status, genotype, censoring — not a diagram. See our hereditary cancer risk assessment guide.
• Mendelian inheritance calculators. The pedigree topology drives autosomal dominant, autosomal recessive, and X-linked recessive probabilities. See our Mendelian inheritance calculator guide. CloudAiry identifies inheritance patterns; Evagene additionally computes probabilities.
• Disease ontology. ICD-10 / OMIM coding against a curated 200-plus disease catalogue, so the pedigree speaks to EHRs, registries, and billing systems without free-text parsing.
• Batch risk screening. Screen a proband across all catalogued diseases simultaneously, flagging where family history crosses a clinical threshold.
• Consanguinity detection. Wright's coefficient of inbreeding from pedigree topology — material for reproductive counselling.
• Karyogram viewer. Standard ISCN karyotype display integrated with the pedigree.
• Clinical report generation. Four distinct report types formatted for the medical record.
• Clinical interoperability. GEDCOM 5.5.1, 23andMe, a scoped REST API, HMAC-signed webhooks, and an embeddable viewer for patient portals and EHR layers. See GEDCOM pedigree software and clinical genetics pedigree tools.
• BYOK LLM governance. Keeping clinical text inside your own contractual boundary with Anthropic or OpenAI, rather than passing through a vendor-hosted model layer.

CloudAiry's security credentials (SOC 2 Type II, ISO 27001, GDPR) are useful and genuinely above-category, but compliance frameworks are necessary rather than sufficient for clinical genetics work. A compliant platform without a clinical data model is still not a clinical platform.

When CloudAiry is genuinely the right tool

Several use cases fit CloudAiry well:

• Biology and genetics teaching. A teacher preparing course material or a tutorial needs a quick, attractive pedigree with an obvious inheritance pattern, and CloudAiry's AI generation is a legitimate time-saver.
• Medical student illustration. Coursework figures, case-study examples, USMLE-style illustrations — an AI-generated pedigree is often better than a hand-drawn one and is explicitly what CloudAiry is built for.
• Research figure drafting. Where the pedigree will be a figure in a paper or poster rather than part of a clinical record, CloudAiry's quick generation and PNG / PDF export are a good fit.
• Professional visual communication. Slide decks, explanatory blog posts, conference talks — the diagram is the deliverable and does not need to support downstream clinical logic.
• Early-stage exploration. Sketching what a family might look like before moving to a clinical platform for the structured record.

If any of these describes your primary use, CloudAiry is a reasonable choice and the rest of this page is not directed at you.

When a clinical-grade tool is the right call

Switch to a clinical platform if any of the following apply:

• The pedigree informs a clinical decision — testing, surveillance, referral, reproductive counselling — and must therefore be auditable, structured, and consistent.
• You need BRCAPRO, MMRpro, or PancPRO carrier and risk estimation, or Mendelian inheritance probability computation beyond pattern recognition.
• You must record diseases using structured codes (ICD-10, OMIM) for EHR, registry, and billing interoperability.
• Your data governance requires BYOK LLM inference, encryption at rest, scoped API access, audit logging, and a clear contractual basis for handling genetic family data.
• You need the pedigree to flow into other systems via REST API, webhooks, MCP, or an embeddable viewer — for patient portals, EHR integration layers, or internal clinical tooling.
• You need GEDCOM or 23andMe imports to bring structured pedigree data in from other systems.
• You run multi-clinician case review where the pedigree is the authoritative clinical record.

A useful test: if your pedigree could be fully reconstructed from the generated PNG or PDF alone, an AI diagramming tool is sufficient. If the pedigree carries structured clinical meaning (disease codes, age at diagnosis, risk model outputs) that the picture cannot express, you need a clinical platform.

Migrating from CloudAiry to Evagene

Moving clinically relevant pedigrees out of CloudAiry is straightforward. Export each pedigree from CloudAiry as PNG or PDF — both are supported — and import into Evagene using pedigree image OCR. The OCR engine recovers individuals, relationships, and visible affected-status annotations from the image, and you finish the structured annotation with ICD-10 / OMIM disease codes, dates, and clinical notes. A typical five-to-seven-generation pedigree takes a few minutes to bring across.

If the underlying data for the pedigree already exists in a structured form (GEDCOM, JSON, 23andMe), skip the image round trip and import those formats directly into Evagene.

CloudAiry and Evagene can coexist. Use CloudAiry for teaching, research figures, and educational prototypes; use Evagene for clinical cases where the pedigree is a structured record, risk models need to run, and AI interpretation drafts a report suitable for the medical record.

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