Count vs Delphina
Comprehensive side-by-side comparison — features, pricing, performance, and more.
Trust & Reliability
Delphina
Too Close to Call
Delphina (6.7) vs Count (6.6) — difference of 0.1 points
Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →
Count
6.6
avg score
Delphina
6.7
avg score
Both tools score very similarly overall — the best choice depends on your specific priorities.
Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →
Too close to call — it's a tie
Count
Delphina
* Verdict is based on our algorithmic scoring of publicly available data. Learn about our methodology
Count is best for
Delphina is best for
Filter by your use case:
Limitations
CountCons
- Free tier is limited to 1 project, 3 canvases, and 5 users
- Free tier has daily AI credit limits and limited models
- Free tier allows only 1 database/MCP connection and 2 automations
- No model training on user data, which may limit custom model fine-tuning
- Output generated by AI is error-prone and not verified by Count for accuracy
- Count AI is not intended to substitute for properly trained and licensed individuals
DelphinaCons
- Pro plan has a user limit of 10 users
- AWS VPC deployment is an add-on feature for Enterprise plan only
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Dimension Comparison
Count
6.6
/ 10
Delphina
6.7
/ 10
Dimension Breakdown
Ease of Use
AIHow intuitive is onboarding, UI navigation, and day-to-day usage for the target audience?
Customization
CalculatedHow much can users tailor workflows, settings, prompts, or outputs to their needs?
Support
AIHow strong is the documentation, customer support, community, and learning resources?
Integration
CalculatedHow well does it connect with other tools, APIs, and workflows?
Compliance & Data Protection
CalculatedCompliance certifications and data-protection posture, counted from ten verified signals: SOC 2 Type II, GDPR compliance, HIPAA, WCAG AA/AAA, PII redaction, licensed-only training, a published sub-processor list, a downloadable DPA, not training on user data, and a documented deletion path
Performance
CalculatedLatency + throughput speed
Planning Quality
CalculatedMulti-step planning depth + replanning capability
Calculated = derived from structured signals (integration count, API/open-source config, compliance certs, response-time). AI = LLM-assessed from public website content. Methodology
Task Performance
Count
Task
Delphina
* Task scores (1–10) are algorithmically generated from publicly available data.