mjsushanth.github.io/finsights.html at main · mjsushanth/mjsushanth.github.io · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>FinSights - Joel Markapudi</title>
    <style>
        * {
            margin: 0;
            padding: 0;
            box-sizing: border-box;
        }

        body {
            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif;
            line-height: 1.6;
            color: #333;
            background: #f5f5f0;
        }

        .container {
            max-width: 920px;
            margin: 0 auto;
            padding: 50px 30px 40px 30px;
            background: #fafaf5;
            min-height: 100vh;
        }

        .back-link {
            display: inline-flex;
            align-items: center;
            color: #4a90e2;
            text-decoration: none;
            margin-bottom: 30px;
            font-size: 0.95rem;
            transition: color 0.3s;
        }

        .back-link:hover {
            color: #357abd;
        }

        h1 {
            font-size: 2.2rem;
            font-weight: 400;
            margin-bottom: 18px;
            color: #2c2c2c;
            line-height: 1.3;
        }

        .project-overview {
            color: #555;
            font-size: 1.05rem;
            margin-bottom: 25px;
            padding-bottom: 20px;
            border-bottom: 2px solid #e0e0d8;
            line-height: 1.7;
        }

        .highlights {
            margin-top: 25px;
        }

        .highlights ul {
            list-style: none;
            margin: 0;
            padding: 0;
        }

        .highlights li {
            margin-bottom: 16px;
            padding-left: 20px;
            position: relative;
            color: #555;
            line-height: 1.7;
        }

        .highlights li:before {
            content: "•";
            position: absolute;
            left: 0;
            color: #4a90e2;
            font-weight: bold;
            font-size: 1.2rem;
        }

        strong {
            color: #2c2c2c;
            font-weight: 500;
        }

        .external-links {
            margin-top: 35px;
            padding-top: 25px;
            border-top: 1px solid #e0e0d8;
        }

        .external-links h2 {
            font-size: 1.3rem;
            font-weight: 500;
            margin-bottom: 15px;
            color: #2c2c2c;
        }

        .external-links a {
            display: inline-block;
            margin-right: 20px;
            margin-bottom: 10px;
            color: #4a90e2;
            text-decoration: none;
            font-size: 1rem;
            transition: color 0.3s;
        }

        .external-links a:hover {
            color: #357abd;
            text-decoration: underline;
        }

        @media (max-width: 768px) {
            .container {
                padding: 35px 20px;
            }

            h1 {
                font-size: 1.8rem;
            }
        }
    </style>
</head>
<body>
    <div class="container">
        <a href="index.html" class="back-link">← Back to Portfolio</a>

        <h1>FinSights: Production-Grade Financial Intelligence System</h1>

        <div class="project-overview">
            Hybrid dual-path RAG system combining structured SQL queries (DuckDB dimension tables) with semantic vector retrieval. Processes 72M→1M sentences via stratified sampling with temporal weighting across regulatory eras, achieving $0.017/query cost with no managed database overhead.
        </div>

        <div class="highlights">
            <ul>
                <li><strong>Data Engineering Pipeline:</strong> 30+ DuckDB SQL scripts implementing weighted multi-objective scoring, fuzzy entity matching, and conditional temporal stratification across company-year-section dimensions</li>

                <li><strong>Advanced RAG Architecture:</strong> Sentence-level embeddings with multi-query expansion, window-hopping retrieval (±3 context sentences), and citation provenance via document headers for exact source traceability</li>

                <li><strong>Evaluation Framework:</strong> Three-tier validation with deterministic gold sets (P1/P2 anchor tests achieving 82% Hit@5, P3 business-realistic suite), BERTScore 0.826 semantic alignment, and bias detection across section/year/filter regime slices</li>

                <li><strong>Production Infrastructure:</strong> AWS S3 Vectors, Bedrock LLM synthesis, Polars/Parquet logging pipeline, and serverless-ready three-tier architecture (FastAPI + Streamlit + ML orchestrator)</li>

                <li><strong>Cost Optimization:</strong> Approximated $0.05/month infrastructure, instead of expensive, managed vector databases, achieved through stratified sampling, metadata filter pushdown (50% query cost savings), and S3-native storage patterns</li>
            </ul>
        </div>

        <div class="external-links">
            <h2>Project Resources</h2>
            <a href="https://github.com/Finsights-MLOps/FinSights/blob/main/README.md" target="_blank">→ Full Documentation</a>
            <a href="https://github.com/Finsights-MLOps/FinSights" target="_blank">→ GitHub Repository</a>
        </div>
    </div>
</body>
</html>