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| <title>PaperHawk — AMD Developer Hackathon Slide Deck</title> |
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| font-size: 13.5px; |
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| |
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| |
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| gap: 8px; |
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| |
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| margin-top: 32px; |
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| color: white; |
| border-radius: 6px; |
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| justify-content: space-around; |
| align-items: center; |
| font-size: 12.5px; |
| font-family: 'JetBrains Mono', monospace; |
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| .builders-meta strong { color: var(--amd-orange); } |
| |
| |
| .team-grid { |
| display: grid; |
| grid-template-columns: repeat(3, 1fr); |
| gap: 18px; |
| margin-top: 32px; |
| } |
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| border-radius: 6px; |
| border-top: 4px solid var(--amd-red); |
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| letter-spacing: 0.12em; |
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| margin-bottom: 10px; |
| letter-spacing: -0.01em; |
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| line-height: 1.5; |
| color: var(--text-muted); |
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| |
| .closing-tagline { |
| margin-top: 28px; |
| padding: 24px; |
| background: var(--paperhawk-black); |
| color: white; |
| text-align: center; |
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| |
| |
| @page { |
| size: 1280px 720px; |
| margin: 0; |
| } |
| @media print { |
| html, body { background: white; } |
| .slide { |
| margin: 0; |
| box-shadow: none; |
| page-break-after: always; |
| } |
| .slide:last-child { page-break-after: auto; } |
| } |
| </style> |
| </head> |
| <body> |
|
|
| |
| |
| |
| <section class="slide slide-cover"> |
| <div class="slide-label">AMD Developer Hackathon × lablab.ai · May 2026</div> |
| <img src="../../paperhawk.jpeg" alt="PaperHawk hero" class="hawk-image"> |
| <h1 class="slide-title">Paper<span class="accent">Hawk</span></h1> |
| <p class="slide-subtitle">Multi-agent document intelligence on AMD Instinct MI300X.<br>Built by engineers who ship.</p> |
| <div class="meta"> |
| <div class="meta-team"> |
| <span><strong>Vince Nándorfi</strong></span> |
| <span><strong>Tamás Vitai</strong></span> |
| <span><strong>Gábor Murcsik</strong></span> |
| </div> |
| <div>Team CsimpiCsirkek · MIT</div> |
| </div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">The Problem</div> |
| <h1 class="slide-title">RAG <span class="accent">retrieves</span>.<br>Audit <span class="accent">finds</span>.</h1> |
| <p class="slide-subtitle">Today's RAG chatbots can do the first. They cannot do the second.</p> |
| <div class="problem-grid"> |
| <div class="problem-card left"> |
| <h3>What RAG does well</h3> |
| <p>Chunk a document. Embed the chunks. Retrieve top-K passages. Generate an answer with the retrieved context.</p> |
| <p>Great for FAQ chatbots. Great for Q&A on a single document.</p> |
| </div> |
| <div class="problem-card right"> |
| <h3>What auditors actually need</h3> |
| <p>"Does the supplier in Invoice #7 match the vendor in PO #3? Is the VAT rate consistent across the package? Any change-of-control clauses? Sanctions hits?"</p> |
| <p>These questions live in the <em>relationship</em> between documents — not in any single chunk.</p> |
| </div> |
| </div> |
| <div class="slide-footer"><span>02 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">What We Built</div> |
| <h1 class="slide-title">A <span class="accent">multi-agent</span> system.<br>Not a retrieval pipeline.</h1> |
| <p class="slide-subtitle">LangGraph 0.6-native. Production-shaped. Open source under MIT.</p> |
| <div class="stat-grid"> |
| <div class="stat-card"><div class="stat-value">4</div><div class="stat-label">Compiled<br>graphs</div></div> |
| <div class="stat-card"><div class="stat-value">6</div><div class="stat-label">Reusable<br>subgraphs</div></div> |
| <div class="stat-card"><div class="stat-value">14</div><div class="stat-label">Deterministic<br>domain checks</div></div> |
| <div class="stat-card"><div class="stat-value">5+1</div><div class="stat-label">Anti-halluc<br>layers</div></div> |
| <div class="stat-card"><div class="stat-value">5</div><div class="stat-label">Agentic<br>chat tools</div></div> |
| </div> |
| <p style="margin-top: 36px; font-size: 14px; color: var(--text-muted); line-height: 1.65;"> |
| Send-API parallelism · <code style="background:var(--bg-cream); padding:2px 6px; border-radius:3px; font-family:'JetBrains Mono', monospace; font-size:12px; color:var(--qwen-purple);">AsyncSqliteSaver</code> checkpointer · <code style="background:var(--bg-cream); padding:2px 6px; border-radius:3px; font-family:'JetBrains Mono', monospace; font-size:12px; color:var(--qwen-purple);">configurable_alternatives</code> provider stack (vLLM / Ollama / dummy) · multi-agent DD assistant with 4 specialists + supervisor + synthesizer · Streamlit 5-tab UI · 61 tests passing in CI without an LLM. |
| </p> |
| <div class="slide-footer"><span>03 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">The Pipeline</div> |
| <h1 class="slide-title">Five steps. <span class="accent">End-to-end.</span></h1> |
| <p class="slide-subtitle">Every step is a typed Pydantic-state node. Every LLM call has structured output.</p> |
| <div class="pipeline-ribbon"> |
| <div class="pipeline-step"> |
| <div class="step-num">1</div> |
| <div class="step-name">Ingest</div> |
| <div class="step-desc">PDF · DOCX · image. Vision-first OCR fallback for scanned pages.</div> |
| </div> |
| <div class="pipeline-step"> |
| <div class="step-num">2</div> |
| <div class="step-name">Classify</div> |
| <div class="step-desc">6-way doc-type classifier. ISA 500 evidence-quality score.</div> |
| </div> |
| <div class="pipeline-step"> |
| <div class="step-num">3</div> |
| <div class="step-name">Extract</div> |
| <div class="step-desc">Pydantic schema per doc-type. _quotes + _confidence per field.</div> |
| </div> |
| <div class="pipeline-step"> |
| <div class="step-num">4</div> |
| <div class="step-name">Cross-ref</div> |
| <div class="step-desc">3-way matching. Package-level analyzer. DD multi-agent.</div> |
| </div> |
| <div class="pipeline-step"> |
| <div class="step-num">5</div> |
| <div class="step-name">Risk + Report</div> |
| <div class="step-desc">14 checks (parallel Send) · LLM ensemble · 3-layer filter · DOCX export.</div> |
| </div> |
| </div> |
| <p style="margin-top: 56px; font-size: 14px; color: var(--text-muted); text-align: center; font-style: italic;"> |
| On AMD MI300X with Qwen 2.5 14B: <strong style="color:var(--amd-red); font-style: normal;">30–90 seconds</strong> end-to-end per package. |
| </p> |
| <div class="slide-footer"><span>04 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">Beyond LLMs · Deterministic Reasoning</div> |
| <h1 class="slide-title">Fourteen rules. <span class="accent">In Python.</span></h1> |
| <p class="slide-subtitle">Every check is a typed Protocol, not a prompt. Run in parallel via the LangGraph Send API.</p> |
| <div class="domain-categories"> |
| <div class="domain-cat tier-a"> |
| <h3>Tier A — Audit · 6 checks</h3> |
| <ul> |
| <li><strong>ISA 500</strong> Evidence hierarchy</li> |
| <li><strong>ISA 320</strong> Materiality threshold</li> |
| <li><strong>ISA 240</strong> Duplicate invoice detector</li> |
| <li><strong>ISA 240</strong> Rounded-amount anomaly</li> |
| <li><strong>Tax-ID CDV</strong> mod-11 checksum</li> |
| <li><strong>Mandatory fields</strong> Invoice completeness</li> |
| </ul> |
| </div> |
| <div class="domain-cat tier-b"> |
| <h3>Tier B — Compliance · 4 checks</h3> |
| <ul> |
| <li><strong>GDPR Art. 28</strong> Sub-processor clause</li> |
| <li><strong>AML / Sanctions</strong> EU + OFAC fuzzy match</li> |
| <li><strong>M&A red flag</strong> Change-of-control · auto-renewal</li> |
| <li><strong>Disproportionality</strong> Penalty-vs-value ratio</li> |
| </ul> |
| </div> |
| <div class="domain-cat tier-c"> |
| <h3>Tier C — Standards · 4 checks</h3> |
| <ul> |
| <li><strong>Incoterms 2020</strong> 11-rule recognizer</li> |
| <li><strong>IFRS / GAAP</strong> Goodwill + lease anomaly</li> |
| <li><strong>Math validation</strong> Net + VAT + gross</li> |
| <li><strong>Contract completeness</strong> 6-key-clause check</li> |
| </ul> |
| </div> |
| </div> |
| <p style="margin-top: 28px; font-size: 13px; color: var(--text-muted); text-align: center; font-style: italic;"> |
| Jurisdiction-aware: locale-specific rules trigger only on locale-tagged inputs. Universal rules run everywhere. |
| </p> |
| <div class="slide-footer"><span>05 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">Trust by Design</div> |
| <h1 class="slide-title">Anti-halluc <span class="accent">5+1</span>. DD <span class="qwen-accent">multi-agent</span>.</h1> |
| <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 32px; margin-top: 28px;"> |
| <div> |
| <div class="col-header" style="color: var(--amd-red);">5+1 layers, every output</div> |
| <div class="layers"> |
| <div class="layer"><div class="layer-num">1</div><div class="layer-text"><code>temperature=0</code> on every LLM call</div></div> |
| <div class="layer"><div class="layer-num">2</div><div class="layer-text"><code>_quotes</code> verbatim source citation</div></div> |
| <div class="layer"><div class="layer-num">3</div><div class="layer-text"><code>_confidence</code> per extracted field</div></div> |
| <div class="layer"><div class="layer-num">4</div><div class="layer-text">Plausibility validators (math · dates · ranges)</div></div> |
| <div class="layer"><div class="layer-num">5</div><div class="layer-text">3-layer LLM-risk filter chain</div></div> |
| <div class="layer plus-one"><div class="layer-num">+1</div><div class="layer-text">Quote validator: drops claims whose quotes aren't in the doc</div></div> |
| </div> |
| </div> |
| <div> |
| <div class="col-header" style="color: var(--qwen-purple);">DD supervisor pattern</div> |
| <div class="dd-flow"> |
| <div class="dd-specialists"> |
| <div class="dd-specialist">Audit specialist</div> |
| <div class="dd-specialist">Legal specialist</div> |
| <div class="dd-specialist">Compliance specialist</div> |
| <div class="dd-specialist">Financial specialist</div> |
| </div> |
| <div class="dd-arrow">↓</div> |
| <div class="dd-supervisor">Supervisor — routing & coordination</div> |
| <div class="dd-arrow">↓</div> |
| <div class="dd-synthesizer">Synthesizer → Executive Summary</div> |
| </div> |
| <p style="font-size: 13px; color: var(--text-muted); margin-top: 18px; line-height: 1.5;"> |
| Four specialists read the same package independently. The supervisor coordinates routing. The synthesizer writes a 3-paragraph executive brief with cited red flags. |
| </p> |
| </div> |
| </div> |
| <div class="slide-footer"><span>06 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">The Stack</div> |
| <h1 class="slide-title">Qwen on <span class="accent">AMD MI300X</span> via vLLM.</h1> |
| <p class="slide-subtitle">192 GB HBM3. ROCm-native. Open-source models, end-to-end.</p> |
| <div class="stack-vertical"> |
| <div class="stack-row"> |
| <div class="stack-label">Streamlit · 5-tab UI</div> |
| <div class="stack-detail">Upload · Results · Chat · DD · Report</div> |
| </div> |
| <div class="stack-row"> |
| <div class="stack-label">LangGraph 0.6 orchestration</div> |
| <div class="stack-detail">4 graphs · 6 subgraphs · Send API · AsyncSqliteSaver</div> |
| </div> |
| <div class="stack-row qwen-row"> |
| <div class="stack-label">Qwen 2.5 14B Instruct (open source)</div> |
| <div class="stack-detail">tool-calling · structured-output · multilingual</div> |
| </div> |
| <div class="stack-row"> |
| <div class="stack-label">vLLM continuous batching</div> |
| <div class="stack-detail">--api-key · --max-model-len 32768 · OpenAI-compatible</div> |
| </div> |
| <div class="stack-row amd-row"> |
| <div class="stack-label">AMD Instinct MI300X · ROCm</div> |
| <div class="stack-detail">192 GB HBM3 · BF16 / FP8 · AMD Developer Cloud</div> |
| </div> |
| <div class="stack-row"> |
| <div class="stack-label">Hugging Face Spaces deploy</div> |
| <div class="stack-detail">lablab-ai-amd-developer-hackathon · Streamlit SDK</div> |
| </div> |
| </div> |
| <div class="slide-footer"><span>07 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">See It In Action</div> |
| <h1 class="slide-title">Three <span class="accent">one-click</span> demos.</h1> |
| <p class="slide-subtitle">Bundled in the repo. Drivable from the Streamlit Upload tab in 30 seconds.</p> |
| <div class="demo-grid"> |
| <div class="demo-card"> |
| <h3>Audit Demo</h3> |
| <p>Three invoices from the same supplier. The March one is 50% pricier than January and February.</p> |
| <div class="demo-result">→ ISA 240 over-billing pattern flagged with cited line items.</div> |
| </div> |
| <div class="demo-card"> |
| <h3>DD Demo</h3> |
| <p>NDA + service agreement + amendment in an acquisition scenario.</p> |
| <div class="demo-result">→ Hidden change-of-control + auto-renewal red flags.</div> |
| </div> |
| <div class="demo-card"> |
| <h3>Compliance Demo</h3> |
| <p>Two contracts; one is missing GDPR Article 28 sub-processor language.</p> |
| <div class="demo-result">→ Domain check #8 detects the gap with regulatory citation.</div> |
| </div> |
| </div> |
| <div class="demo-time-banner"> |
| On AMD MI300X with Qwen 2.5 14B Instruct: <strong>30–90 seconds</strong> per package · end-to-end · with citations. |
| </div> |
| <div class="slide-footer"><span>08 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">Open · Reproducible · Public</div> |
| <h1 class="slide-title">Built <span class="accent">for builders</span>.</h1> |
| <p class="slide-subtitle">MIT licensed. Reproducible from a clean clone. No closed weights, no proprietary extensions.</p> |
| <div class="builders-grid"> |
| <div class="builders-card"> |
| <div class="marker">/ 01</div> |
| <h3>Open source · MIT</h3> |
| <p>Public GitHub repo. No "training data not included" footnotes. Clone it, run it, fork it. The whole codebase is yours to read.</p> |
| </div> |
| <div class="builders-card"> |
| <div class="marker">/ 02</div> |
| <h3>Reproducible</h3> |
| <p>Same stack from laptop to MI300X. <code>infra/vllm/Dockerfile</code> + <code>serve.sh</code> + <code>requirements.txt</code>. One command, one container.</p> |
| </div> |
| <div class="builders-card"> |
| <div class="marker">/ 03</div> |
| <h3>Battle-tested</h3> |
| <p>61 tests passing in CI without any LLM. Deterministic dummy provider for CI; vLLM and Ollama for everything else.</p> |
| </div> |
| </div> |
| <div class="builders-meta"> |
| <span><strong>github.com/nandorfivince/paperhawk</strong></span> |
| <span style="color: rgba(255,255,255,0.3);">|</span> |
| <span><strong>HF Space:</strong> lablab-ai-amd-developer-hackathon/paperhawk</span> |
| <span style="color: rgba(255,255,255,0.3);">|</span> |
| <span><strong>License:</strong> MIT</span> |
| </div> |
| <div class="slide-footer"><span>09 / 10</span><span>PaperHawk · AMD × lablab.ai</span></div> |
| </section> |
|
|
| |
| |
| |
| <section class="slide"> |
| <div class="slide-label">The Team</div> |
| <h1 class="slide-title">Three engineers.<br>One <span class="accent">shipped product</span>.</h1> |
| <p class="slide-subtitle">We've shipped together for nearly a decade. PaperHawk is what happens when domain knowledge, engineering rigor, and product instinct meet on the same codebase.</p> |
| <div class="team-grid"> |
| <div class="team-card"> |
| <div class="team-role">Lead · LangGraph · AMD Adaptation</div> |
| <div class="team-name">Vince Nándorfi</div> |
| <div class="team-desc">System architecture, domain research, ROCm/vLLM adaptation, testing. PaperHawk's blueprint and the AMD-edition rewrite.</div> |
| </div> |
| <div class="team-card"> |
| <div class="team-role">Engineering · DevOps</div> |
| <div class="team-name">Tamás Vitai</div> |
| <div class="team-desc">Senior++ engineer. Implementation, infrastructure, integration testing. Where the code meets the runtime.</div> |
| </div> |
| <div class="team-card"> |
| <div class="team-role">Engineering · Algorithms</div> |
| <div class="team-name">Gábor Murcsik</div> |
| <div class="team-desc">Engineering rigor. Algorithmic precision. Senior systems thinking, sharpened over years of complex production builds.</div> |
| </div> |
| </div> |
| <div class="closing-tagline"> |
| <p>Beyond simple <span class="accent">RAG</span>. Built to <span class="qwen-accent">ship</span>.</p> |
| </div> |
| <div class="slide-footer"><span>10 / 10</span><span>Team CsimpiCsirkek · MIT · github.com/nandorfivince/paperhawk</span></div> |
| </section> |
|
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