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Dermsquared Polaris

Real-time clinical answers for dermatology professionals

TL;DR

01

Built Polaris, an AI-powered search engine trained on Dermsquared's 20+ year content library, enabling dermatologists to get real-time answers to clinical questions without disrupting their workflow

02

Developed a hybrid AI and keyword search pipeline that categorizes clinical inquiries in milliseconds, routes them to specialized knowledge bases, and returns clinically relevant answers with supporting content

03

Designed an automated content ingestion pipeline that continuously indexes new dermatological content, including videos, podcasts, CME materials, case studies, and drug documentation, keeping clinical knowledge current

The Challenge

Dermatologists face a daily problem of information overload. Staying current with treatment protocols, drug interactions, access management workflows, and emerging research requires constant effort. When a clinical question arises mid-appointment or during documentation, there is no fast, reliable way to search a trusted dermatology knowledge base without context-switching to general search engines that surface generic, unvetted results.

Dermsquared had spent over 20 years building one of the most comprehensive repositories of dermatology-specific content, including expert videos, podcasts, conference proceedings, CME materials, case studies, and drug documentation. But that content was fragmented across the platform and not optimized for fast, conversational retrieval. Users could browse or scroll, but not simply ask a clinical question and get a direct, authoritative answer.

Traditional keyword search returns lists of results, but dermatologists need answers. A physician asking about systemic medication approval workflows or appropriate treatments for a teenage acne patient needs a synthesized response grounded in vetted clinical content, not ten links to sort through manually.

Dermsquared needed a search experience that could function as a digital clinical assistant, one that understood the intent behind clinical queries, pulled from verified expert content, and surfaced related resources in a way that felt native to how physicians actually work.

Key Results

01

Launched publicly March 2024 following staged rollout with pilot user testing

02

Content library spans 20+ years of expert dermatology content across articles, videos, podcasts, CME materials, case studies, and drug documentation

03

Query classification routes requests to specialized knowledge bases in milliseconds

04

Automated pipeline continuously indexes new content without manual intervention

05

Expanded in v2 to cover 100% of Dermsquared's public-facing website content

06

Powers the platform content recommender on video and podcast pages

The Solution

01

AI-Augmented Search Built on Proprietary Clinical Content

Standard search engines are not built for clinical precision. AE Studio built Polaris as an AI-augmented search engine specifically trained on Dermsquared's proprietary content library, accumulated over more than two decades of expert-driven dermatology education.

The system goes beyond keyword matching. Polaris interprets the intent behind clinical questions, categorizes the query type in milliseconds, and routes it to the appropriate knowledge base before generating a synthesized, clinically grounded response.

02

Query Classification and Specialized Routing

Not all clinical questions are the same. A question about Chronic Spontaneous Urticaria symptoms requires a different retrieval strategy than a question about navigating prior authorization for systemic medications.

Polaris uses precision-targeted algorithms to classify queries into categories, including clinical questions, practice management topics, access management workflows, and conference-specific content. Each category triggers a specialized prompt strategy, ensuring that the response is calibrated to the nuance of what the physician is actually asking.

This classification layer also enables Polaris to recognize when a question falls outside its knowledge base and return an honest, non-hallucinatory response rather than fabricating an answer.

03

Hybrid AI and Keyword Search

Polaris combines AI-generated responses with traditional keyword search results, giving physicians both a synthesized answer and access to all related source material. This hybrid approach preserves the depth of Dermsquared's content library while providing the immediacy that clinical contexts demand.

Search results surface related articles, videos, podcasts, and conference materials alongside the AI response, creating a seamless experience where users can go deeper on any topic without leaving the platform.

04

Automated Content Ingestion Pipeline

Clinical knowledge evolves constantly. A search engine trained on static content quickly becomes outdated. AE Studio built an automated content pipeline that continuously indexes new dermatological content as it is published on Dermsquared, including news articles, research findings, podcast transcripts, video content, CME materials, case studies, and drug documentation.

This pipeline ensures that Polaris always reflects the current state of Dermsquared's knowledge base without manual intervention. When new expert content is added, it becomes searchable through Polaris automatically.

05

Clinical Accuracy Guardrails

In clinical settings, inaccurate information is not just unhelpful, it can be harmful. AE Studio implemented multi-layer verification within Polaris to validate AI responses against trusted dermatological sources and eliminate hallucinations.

The system is designed to recognize the boundaries of its knowledge. Polaris only answers questions it can ground in verified Dermsquared content. Non-clinical or out-of-scope queries are handled gracefully, with the system indicating when a topic falls outside its knowledge base.

06

Polaris v2: Expanding to the Full Knowledge Base

Following the successful v1 launch, AE Studio partnered with Dermsquared to expand Polaris to cover 100% of the platform's public-facing content. Polaris v2 extended content mapping beyond the initial library of articles and media to include the entire Dermsquared website, from practice management pages to condition-specific resources.

V2 also introduced a restructured prompt strategy that identifies the category of a search query first, then applies a specialized prompt for that category. This architecture allows future capabilities to be layered in without disrupting established features, making Polaris extensible as Dermsquared's content and physician needs continue to evolve.

07

Content Diversity and Related Resource Discovery

Beyond delivering direct answers, Polaris functions as a content discovery layer across the Dermsquared platform. After returning a clinical response, the system surfaces related videos, podcasts, research articles, and conference content, keeping physicians connected to the broader Dermsquared knowledge ecosystem.

This related content surfacing increases dwell time on the platform, drives engagement with content types physicians might not have discovered through browsing, and reinforces Dermsquared's value as the definitive professional resource for dermatology.

Results

Key Metrics

Launched publicly March 2024 following staged rollout with pilot user testing

Content library spans 20+ years of expert dermatology content across articles, videos, podcasts, CME materials, case studies, and drug documentation

Query classification routes requests to specialized knowledge bases in milliseconds

Automated pipeline continuously indexes new content without manual intervention

Expanded in v2 to cover 100% of Dermsquared's public-facing website content

Powers the platform content recommender on video and podcast pages

The Full Story

Polaris launched publicly in March 2024 following a staged rollout that began with a soft launch under a feature flag for pilot users. The release was coordinated across Dermsquared's stakeholder teams with a full release management process, including production testing, release communications, and post-launch monitoring.

The platform now serves dermatologists, PAs, NPs, and other dermatology professionals across Dermsquared's physician community, delivering real-time clinical answers through a search experience embedded directly in the site header. Physicians can ask clinical questions, practice management questions, and drug-related questions and receive synthesized responses grounded in Dermsquared's curated expert content.

Beyond search, Polaris powers Dermsquared's content recommendation system, surfacing related materials on video and podcast pages to deepen engagement with expert content across the platform. The AI-powered recommender replaced the prior static recommendation logic, creating a more personalized content discovery experience.

Polaris has become a core platform feature, with subsequent development phases adding JofSkin journal content to the search index, integrating Drug Detail Pages as a knowledge source, and enabling sponsored content placements within search results to unlock new revenue opportunities for Dermsquared.

Conclusion

Polaris transformed Dermsquared's content library from a resource physicians had to browse into one they could simply ask. By combining AI-augmented search with clinical accuracy guardrails, automated content ingestion, and intelligent query routing, AE Studio delivered a tool that fits naturally into the dermatologist's workflow.

The platform launched on time, scaled from a pilot cohort to the full Dermsquared physician community, and evolved through multiple versions to cover the entire knowledge base. Polaris now functions as both a search engine and a content discovery layer, surfacing related expert content alongside every clinical answer and deepening physician engagement with Dermsquared's 20+ year library.

For a platform built on the depth and authority of its expert content, Polaris made that depth accessible in real time, at the moment physicians need it most.

Key Insights

1

Clinical AI requires specialized knowledge grounding. General-purpose search engines surface unvetted results. Polaris was built specifically on Dermsquared's verified expert content, giving physicians confidence that responses reflect trusted clinical sources rather than the open web.

2

Query classification before response generation improves precision. Routing clinical, practice management, and institutional questions to category-specific prompts produces more accurate, contextually appropriate answers than a single generalized prompt strategy.

3

Hybrid search preserves depth while adding speed. Combining AI-synthesized responses with full keyword search results gives physicians both an immediate answer and access to the source materials they may want to explore further.

4

Automated content pipelines are essential for clinical relevance. Medical knowledge evolves constantly. An ingestion pipeline that automatically indexes new content ensures that Polaris reflects current clinical guidance without manual curation effort.

5

Clinical accuracy guardrails are non-negotiable. Multi-layer verification and graceful handling of out-of-scope queries prevent hallucinations, which would erode physician trust and undermine the platform's clinical credibility.

6

Phased architecture enables sustainable expansion. Building Polaris with a modular prompt strategy in v2 allowed AE Studio to expand the knowledge base and add new content types without disrupting the existing feature set.

Frequently Asked Questions

Polaris is a retrieval-augmented system, not a generative AI that draws on the open internet. Every response is grounded in Dermsquared's curated library of expert content, accumulated over more than 20 years of dermatology-specific education. Multi-layer verification validates responses against these trusted sources before they are returned to the user. When a question falls outside Polaris's knowledge base, the system returns an honest non-answer rather than fabricating a response.
Polaris handles clinical questions about conditions, symptoms, treatments, and medications, as well as practice management questions about workflows, patient access, and specialty pharmacy resources. It can answer questions about Dermsquared's conference offerings, CME activities, and institutional resources. The system classifies each query into the appropriate category and applies a specialized response strategy tailored to that type of question.
An automated content ingestion pipeline continuously indexes new content published on Dermsquared, including articles, research findings, podcast transcripts, video content, CME materials, case studies, and drug documentation. When new expert content is added to the platform, it becomes searchable through Polaris automatically, without manual curation or retraining cycles.
Standard keyword search returns a ranked list of links. Polaris interprets the intent behind a clinical question and returns a synthesized answer drawn from verified expert content, alongside related articles, videos, and podcasts. The hybrid approach combines AI-generated responses with traditional search results, so physicians get an immediate answer while retaining access to the full depth of Dermsquared's content library.
Polaris is embedded directly into the Dermsquared site header, making it accessible from any page on the platform. It also powers the content recommendation system on video and podcast pages, surfacing related materials based on AI analysis of content relationships. The search index has been extended to include JofSkin journal content and Drug Detail Pages, and sponsored content placements within search results create additional value for Dermsquared's industry partners.
OverviewHealthcareintermediate7 min readAI SearchDermatologyClinical Decision SupportHealthcare AIContent RecommendationRAGKnowledge ManagementEdTech

Published: Jan 2025 ยท Last updated: Feb 2026

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Polaris: AI Search Engine for Dermatology Clinical Questions