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<!doctype html>
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                <h3>Lab Signals</h3>
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                  <strong id="signalRepoCount">--</strong>
                  <span>Public repositories</span>
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                  <span>Total stars</span>
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                  <span>Updated in 90 days</span>
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                  <strong id="signalTopLanguage">--</strong>
                  <span>Top language</span>
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      <section id="focus">
        <div class="container">
          <h2 class="reveal">Focus Areas</h2>
          <p class="section-sub reveal">
            Iridyne operates at the intersection of applied AI and systems engineering, with two clear tracks for execution.
          </p>
          <div class="pillars pillars-2">
            <article class="panel reveal">
              <h3>Medical Multimodal Systems</h3>
              <p>
                Research-to-implementation workflows for multimodal medical intelligence, emphasizing model fusion,
                robustness, and practical usability.
              </p>
            </article>
            <article class="panel reveal">
              <h3>Developer Infrastructure</h3>
              <p>
                Tools and pipelines that improve speed, reproducibility, and quality of engineering work across modern
                AI-native teams.
              </p>
            </article>
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        </div>
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      <section id="advantage">
        <div class="container">
          <h2 class="reveal">Why teams choose Iridyne</h2>
          <p class="section-sub reveal">
            The value is not only model ideas. It is the combination of research depth, engineering discipline, and
            collaboration style that helps work survive contact with real constraints.
          </p>
          <div class="advantage-grid">
            <article class="panel reveal">
              <h3>Research with delivery pressure</h3>
              <p>We care about novelty, but we also design for reproducibility, iteration speed, and eventual deployment.</p>
            </article>
            <article class="panel reveal">
              <h3>Multimodal-first thinking</h3>
              <p>We work comfortably across text, vision, speech, and structured signals instead of treating modalities in isolation.</p>
            </article>
            <article class="panel reveal">
              <h3>Low-friction collaboration</h3>
              <p>We prefer clear scopes, visible milestones, and direct technical communication over vague consulting theater.</p>
            </article>
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      <section id="social-proof">
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          <h2 class="reveal">Social proof that feels technical, not theatrical</h2>
          <p class="section-sub reveal">
            We prefer evidence over slogans. These collaboration signals reflect how teams describe our working style.
          </p>
          <div class="social-strip reveal" aria-label="collaboration signal tags">
            <span class="signal-pill">Research + Engineering</span>
            <span class="signal-pill">Fast Feedback Loops</span>
            <span class="signal-pill">Clear Scope Ownership</span>
            <span class="signal-pill">Reproducible Delivery</span>
          </div>
          <div class="testimonial-grid">
            <article class="panel reveal quote-card">
              <p>
                “Iridyne helped us move from fuzzy multimodal ideas to testable architecture decisions in weeks, not
                quarters.”
              </p>
              <span>— Research Lead, Healthcare AI Team</span>
            </article>
            <article class="panel reveal quote-card">
              <p>
                “The biggest value was execution clarity: concrete milestones, transparent tradeoffs, and no consultant
                fluff.”
              </p>
              <span>— Engineering Manager, Product Infrastructure</span>
            </article>
            <article class="panel reveal quote-card">
              <p>
                “They balance novelty with shipping constraints. That combination is rare and exactly what we needed.”
              </p>
              <span>— Technical Founder</span>
            </article>
          </div>
        </div>
      </section>

      <section id="flagship">
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          <h2 class="reveal">Flagship Projects</h2>
          <p class="section-sub reveal">Representative projects that define current direction and engineering standards.</p>
          <div class="repo-grid flagship-grid">
            <article class="repo-card show reveal">
              <div class="repo-head">
                <a class="repo-name" href="https://github.com/iridyne/medfusion" target="_blank" rel="noreferrer">medfusion</a>
                <span class="chip">Medical AI</span>
              </div>
              <p class="case-line"><strong>Problem</strong> Fragmented multimodal clinical signals.</p>
              <p class="case-line"><strong>Approach</strong> Fusion-first architecture for robust multimodal reasoning.</p>
              <p class="case-line"><strong>Status</strong> Active evolution with production-oriented experiments.</p>
            </article>
            <article class="repo-card show reveal">
              <div class="repo-head">
                <a class="repo-name" href="https://github.com/iridyne/cinnabar" target="_blank" rel="noreferrer">cinnabar</a>
                <span class="chip">Dev Infra</span>
              </div>
              <p class="case-line"><strong>Problem</strong> Privacy and latency limits in voice tooling.</p>
              <p class="case-line"><strong>Approach</strong> Offline-first speech pipeline with lightweight runtime.</p>
              <p class="case-line"><strong>Status</strong> Active optimization for practical local deployment.</p>
            </article>
            <article class="repo-card show reveal">
              <div class="repo-head">
                <a class="repo-name" href="https://github.com/iridyne/prism" target="_blank" rel="noreferrer">prism</a>
                <span class="chip">Tooling</span>
              </div>
              <p class="case-line"><strong>Problem</strong> Inconsistent build and iteration workflows.</p>
              <p class="case-line"><strong>Approach</strong> Pragmatic tooling layer for repeatable engineering loops.</p>
              <p class="case-line"><strong>Status</strong> Actively updated around team execution quality.</p>
            </article>
          </div>
        </div>
      </section>

      <section id="case-studies">
        <div class="container">
          <h2 class="reveal">Case snapshots</h2>
          <p class="section-sub reveal">
            Typical project patterns where collaboration with Iridyne creates measurable movement.
          </p>
          <div class="case-grid">
            <article class="panel reveal case-card">
              <h3>Multimodal clinical triage prototype</h3>
              <p>
                Built a scoped prototype that integrated notes + imaging metadata, established evaluation baselines, and
                reduced iteration uncertainty before full-scale build.
              </p>
            </article>
            <article class="panel reveal case-card">
              <h3>Internal AI tooling acceleration</h3>
              <p>
                Redesigned dev workflow around repeatable prompts, evaluation checkpoints, and local tooling loops,
                improving experiment throughput and handoff quality.
              </p>
            </article>
          </div>
        </div>
      </section>

      <section id="proof">
        <div class="container">
          <h2 class="reveal">Proof</h2>
          <p class="section-sub reveal">
            We prioritize shipping and maintainability over slogans. These signals are fetched directly from public repositories.
          </p>
          <div class="proof-grid reveal">
            <div class="panel">
              <h3 id="proofRepoCount">--</h3>
              <p>Selected repositories in showcase</p>
            </div>
            <div class="panel">
              <h3 id="proofRecentCount">--</h3>
              <p>Repositories updated in 90 days</p>
            </div>
            <div class="panel">
              <h3 id="proofUpdatedRepo">--</h3>
              <p>Most recently shipped repository</p>
            </div>
            <div class="panel">
              <h3 id="proofLanguages">--</h3>
              <p>Top language in active set</p>
            </div>
          </div>
        </div>
      </section>

      <section id="process">
        <div class="container">
          <h2 class="reveal">How collaboration works</h2>
          <p class="section-sub reveal">
            We keep the engagement model simple: align on the problem, validate quickly, then build with clear checkpoints.
          </p>
          <div class="process-grid">
            <article class="step-card reveal">
              <span class="step-index">01</span>
              <h3>Scope the problem</h3>
              <p>Define target users, constraints, available data, risk boundaries, and what success actually looks like.</p>
            </article>
            <article class="step-card reveal">
              <span class="step-index">02</span>
              <h3>Prototype the approach</h3>
              <p>Pressure-test architecture choices early with focused experiments instead of committing to a large blind build.</p>
            </article>
            <article class="step-card reveal">
              <span class="step-index">03</span>
              <h3>Ship the system</h3>
              <p>Turn the validated direction into maintainable code, measurable outputs, and a handoff the team can keep using.</p>
            </article>
          </div>
        </div>
      </section>

      <section id="collaborate">
        <div class="container">
          <h2 class="reveal">Collaborate with Iridyne</h2>
          <p class="section-sub reveal">
            We work with research teams and builders who need rigorous experimentation plus reliable engineering delivery.
          </p>
          <div class="collab-grid reveal">
            <article class="panel">
              <h3>Research Collaboration</h3>
              <p>Co-develop multimodal methods, benchmark design, and reproducible experiment pipelines.</p>
            </article>
            <article class="panel">
              <h3>Engineering Collaboration</h3>
              <p>Build and harden practical AI systems with clear constraints, metrics, and handoff quality.</p>
            </article>
            <article class="panel">
              <h3>Technical Due Diligence</h3>
              <p>Audit model, tooling, and workflow decisions to identify weak spots before they become expensive.</p>
            </article>
            <article class="panel">
              <h3>Internal Tooling Acceleration</h3>
              <p>Design lean developer systems that reduce friction around iteration, evaluation, and local productivity.</p>
            </article>
          </div>
          <div class="cta-row collab-cta reveal">
            <a class="btn btn-primary" href="https://github.com/iridyne" target="_blank" rel="noreferrer">Collaborate on GitHub</a>
            <a class="btn btn-secondary" href="#flagship">Review Flagship Work</a>
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      </section>

      <section id="faq">
        <div class="container">
          <h2 class="reveal">FAQ</h2>
          <p class="section-sub reveal">
            A few quick answers for teams deciding whether the fit is real.
          </p>
          <div class="faq-list">
            <article class="panel reveal">
              <h3>What kind of teams are the best fit?</h3>
              <p>Research groups, AI product teams, and technical founders who need both experimentation quality and pragmatic execution.</p>
            </article>
            <article class="panel reveal">
              <h3>Do you only work on medical AI?</h3>
              <p>Medical multimodal systems are a core strength, but the same engineering discipline also applies to broader AI infrastructure and developer tooling.</p>
            </article>
            <article class="panel reveal">
              <h3>What does a first engagement usually look like?</h3>
              <p>Usually a scoped technical collaboration around one concrete system, workflow bottleneck, or research-to-production bridge.</p>
            </article>
          </div>
        </div>
      </section>

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              View all on GitHub
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