# PII Redaction POC — Solution Guide

Single reference for architecture, NER models, routing, operations, Tamil/Tanglish support, Git setup, and the post-POC improvement backlog.

---

## Table of contents

1. [Purpose](#1-purpose)
2. [Canonical example](#2-canonical-example)
3. [Detection strategies](#3-detection-strategies)
4. [Solution architecture](#4-solution-architecture)
5. [Trust boundary](#5-trust-boundary)
6. [NER models](#6-ner-models)
7. [NER routing — English vs Tamil](#7-ner-routing--english-vs-tamil)
8. [Configuration and dependency injection](#8-configuration-and-dependency-injection)
9. [Running and testing](#9-running-and-testing)
10. [Tamil and Tanglish support](#10-tamil-and-tanglish-support)
11. [Git remote setup (Xenovex)](#11-git-remote-setup-xenovex)
12. [Improvement roadmap](#12-improvement-roadmap)
13. [Key source files](#13-key-source-files)

---

## 1. Purpose

This .NET proof-of-concept intercepts user prompts containing regulated personally identifiable information (PII), redacts sensitive values into stable placeholders, and transmits **only sanitized text** across the LLM trust boundary.

The solution uses:

- Clear layer separation (Core / Infrastructure / hosts)
- Interface-driven composition and dependency injection
- Swappable ONNX NER adapters and `Microsoft.Extensions.AI` chat clients

It targets financial and customer-service workloads where raw PII must not leave the application process when invoking external language models.

---

## 2. Canonical example

With English and Tamil ONNX models loaded (`scripts/download-ner-model.ps1`, `scripts/download-tamil-ner-model.ps1`):

| Stage | Value |
|-------|-------|
| **Input** | `Customer Ravi Kumar with email ravi.kumar@gmail.com and phone 9876543210 has LoanNumber LN-456789 and PAN ABCDE1234F. Please summarize this customer issue.` |
| **Sanitized output** | `Customer <PERSON_1> with email <EMAIL_1> and phone <PHONE_1> has LoanNumber <LOAN_NUMBER_1> and PAN <PAN_1>. Please summarize this customer issue.` |
| **Mock LLM response** | `[Mock LLM Response] Received sanitized prompt (146 chars). No original PII was transmitted.` |

| Type | Value | Source |
|------|-------|--------|
| PERSON | Ravi Kumar | NER |
| EMAIL | ravi.kumar@gmail.com | Regex |
| PHONE | 9876543210 | Regex |
| LOAN_NUMBER | LN-456789 | Domain |
| PAN | ABCDE1234F | Regex |

The placeholder map (`<PERSON_1>` → `Ravi Kumar`, etc.) stays **in-process** and is never sent to the LLM.

---

## 3. Detection strategies

| Strategy | Detects | Rationale |
|----------|---------|-----------|
| **Regex** | Email, phone, PAN, Aadhaar, credit card | Deterministic, format-bound, auditable |
| **ONNX NER** | Person names | Contextual; no rigid format |
| **Domain rules** | Loan number (`LN-`), customer ID (`CID-`), account (`ACC-`) | Business-specific identifiers |

**Overlap resolution** (`CompositePiiDetector`): detectors run in order **Domain → Regex → NER**. On overlapping spans, candidates are sorted by start index, length, and source priority (**Domain 3 > Regex 2 > NER 1**); the first non-overlapping candidate wins.

**Redaction** (`PlaceholderPiiRedactor`): format `<{TYPE}_{n}>`; duplicate values reuse placeholders; replacement is right-to-left to preserve indices.

---

## 4. Solution architecture

### Project structure

```
src/
├── PiiRedaction.ConsoleApp/        # Console demo, DI bootstrap
├── PiiRedaction.TestHarness.Wpf/   # WPF MVVM manual test harness
├── PiiRedaction.Core/              # Detection, redaction, abstractions
└── PiiRedaction.Infrastructure/    # ONNX runners, mock LLM
models/                             # ONNX assets (gitignored)
tests/                              # NUnit unit and integration tests
```

| Project | Layer | Responsibility |
|---------|-------|----------------|
| `PiiRedaction.ConsoleApp` | Presentation | Samples, interactive mode, audit output |
| `PiiRedaction.TestHarness.Wpf` | Presentation | Category-filtered prompts, redact UI, batch runner |
| `PiiRedaction.Core` | Domain | `IPiiDetector`, `IPromptSanitizer`, detectors, models |
| `PiiRedaction.Infrastructure` | Infrastructure | `RoutingOnnxNerModelRunner`, `MockLlmPromptService` |
| `tests/*` | Test | ~112 tests; `RealModel` and `TamilNer` categories |

**Dependency direction:** `ConsoleApp` / `Wpf` → `Infrastructure` → `Core`. Core has no ONNX or LLM SDK references.

### Key abstractions

| Abstraction | Default implementation | Extension |
|-------------|------------------------|-----------|
| `IPiiDetector` | `CompositePiiDetector` | Add detector; register in composite order |
| `IPiiRedactor` | `PlaceholderPiiRedactor` | Hashing, vault tokens |
| `IPromptSanitizer` | `PromptSanitizer` | Orchestrates detect + redact |
| `IOnnxNerModelRunner` | `RoutingOnnxNerModelRunner` | Script-based EN/TA routing |
| `ILlmPromptService` | `MockLlmPromptService` | Production adapter |
| `IChatClient` | `MockChatClient` | Azure OpenAI, etc. |

### Data flow

```mermaid
flowchart TB
    subgraph hosts [Hosts]
        console[ConsoleApp / WpfHarness]
    end

    subgraph core [PiiRedaction.Core]
        sanitizer[PromptSanitizer]
        composite[CompositePiiDetector]
        domain[DomainRulePiiDetector]
        regex[RegexPiiDetector]
        onnxDet[OnnxNerPiiDetector]
        redactor[PlaceholderPiiRedactor]
    end

    subgraph infra [PiiRedaction.Infrastructure]
        router[RoutingOnnxNerModelRunner]
        en[EnglishOnnxNerRunner]
        ta[TamilOnnxNerRunner]
        llm[MockLlmPromptService]
    end

    console --> sanitizer
    sanitizer --> composite
    composite --> domain
    composite --> regex
    composite --> onnxDet
    onnxDet --> router
    router --> en
    router --> ta
    sanitizer --> redactor
    console -->|"sanitized text only"| llm
```

**Pipeline:** `Sanitize` → `Detect` (all detectors) → `Redact` → `SanitizationResult`. Optional: `SendPromptAsync(sanitizedPrompt)` to LLM.

---

## 5. Trust boundary

Only the **sanitized prompt string** crosses `ILlmPromptService` / `IChatClient`. Original PII, entity metadata, and the placeholder map remain in-process.

```mermaid
flowchart LR
    subgraph inProcess [In-Process]
        raw[Original prompt]
        entities[Detected entities]
        map[Placeholder map]
        audit[Console / WPF display]
    end

    subgraph boundary [LLM boundary]
        sanitized[Sanitized prompt only]
    end

    subgraph external [External LLM]
        chat[IChatClient]
    end

    raw --> audit
    entities --> audit
    map --> audit
    sanitized --> chat
    raw -.->|never sent| chat
    map -.->|never sent| chat
```

---

## 6. NER models

Person-name detection is the **only** NER responsibility. Structured PII uses regex and domain rules.

### Routing summary

| Script in prompt | Model(s) | Typical use |
|------------------|----------|-------------|
| `LatinOnly` | English | English names, Indian names in Roman script, **Tanglish** |
| `TamilOnly` | Tamil | Tamil-script names |
| `Mixed` | Both; merge spans | Code-mixed prompts |
| `NoLetters` | Neither | Digits/symbols only |

### English model

| Property | Value |
|----------|-------|
| Hugging Face ID | [`dslim/bert-base-NER`](https://huggingface.co/dslim/bert-base-NER) |
| Tokenizer | WordPiece (`vocab.txt`, `BertWordPieceEncoder`) |
| Person labels | `B-PER`, `I-PER`, `B-PERSON`, `I-PERSON` |
| Primary path | `models/en/ner-model.onnx` |
| Legacy fallback | `models/ner-model.onnx` |
| Download | `.\scripts\download-ner-model.ps1` |

### Tamil model

| Property | Value |
|----------|-------|
| Hugging Face ID | [`prachuryyaIITG/SampurNER_Tamil_IndicBERTv2`](https://huggingface.co/prachuryyaIITG/SampurNER_Tamil_IndicBERTv2) |
| Tokenizer | WordPiece when `vocab.txt` present (export path); SentencePiece fallback |
| Person labels | Any BIO tag containing `person` (case-insensitive) |
| Path | `models/ta/model.onnx` |
| Download | `.\scripts\download-tamil-ner-model.ps1` |

**Why SampurNER over MuRIL:** Tamil-specific NER training, smaller footprint (~0.3B vs ~0.6B), validated ONNX export in this repo. MuRIL reserved as eval-driven fallback.

### Model assets (gitignored)

| Directory | Key files | Approx. size |
|-----------|-----------|--------------|
| `models/en/` | `ner-model.onnx`, `vocab.txt`, `ner-labels.txt` | ~431 MB ONNX |
| `models/ta/` | `model.onnx`, `vocab.txt`, `ner-labels.txt` | ~1 GB ONNX |

Only `models/en/.gitkeep` and `models/ta/.gitkeep` are committed.

### Shared inference

Both runners use `OnnxTokenClassifierRunner`:

- Max sequence length: **128 tokens** (long prompts truncate silently)
- BIO decode → `PiiEntityType.Person` only
- Missing model → fail-open: `[]` from NER (person names not redacted)

---

## 7. NER routing — English vs Tamil

### Call chain

```
PromptSanitizer → CompositePiiDetector → OnnxNerPiiDetector
  → RoutingOnnxNerModelRunner.PredictEntities()
    → ScriptRouter.GetComposition(text)
    → switch (composition) { English / Tamil / both }
    → MergePersonSpans()
```

### Step 1: `ScriptRouter` (Core)

**File:** `src/PiiRedaction.Core/Detection/ScriptRouter.cs`

Single pass over characters:

- Tamil letter: Unicode **U+0B80 – U+0BFF**
- Latin letter: `char.IsAsciiLetter`
- Both seen → `Mixed` (early exit)
- Neither → `NoLetters`
- Otherwise → `TamilOnly` or `LatinOnly`

```csharp
// ScriptComposition enum: LatinOnly, TamilOnly, Mixed, NoLetters
public ScriptComposition GetComposition(string text) { /* scan chars */ }
```

**Tanglish** in Roman script → `LatinOnly` → **English model only**.

### Step 2: `RoutingOnnxNerModelRunner` (Infrastructure)

**File:** `src/PiiRedaction.Infrastructure/Onnx/RoutingOnnxNerModelRunner.cs`

This is the **branch decision**:

| `ScriptComposition` | English | Tamil |
|---------------------|---------|-------|
| `LatinOnly` | Yes if available | No |
| `TamilOnly` | No | Yes if `EnableTamilNer` and available |
| `Mixed` | Yes if available | Yes if `EnableTamilNer` and available |
| `NoLetters` | No | No |

Both models run on the **full prompt text** for `Mixed` (no script segmentation).

### Step 3: Merge

`MergePersonSpans`: overlapping PERSON spans → **longer span wins**; ordered by `StartIndex`.

### Routing diagram

```mermaid
flowchart TD
    text[Prompt text] --> sr[ScriptRouter]
    sr --> latin[LatinOnly]
    sr --> tamil[TamilOnly]
    sr --> mixed[Mixed]
    sr --> none[NoLetters]
    latin --> en[EnglishOnnxNerRunner]
    tamil --> ta[TamilOnnxNerRunner]
    mixed --> en
    mixed --> ta
    en --> merge[MergePersonSpans]
    ta --> merge
    none --> empty[No NER]
```

### Worked examples

| Input style | Composition | Models |
|-------------|---------------|--------|
| `Customer Ravi Kumar…` | `LatinOnly` | English |
| `வாடிக்கையாளர் ராஜேஷ் குமார்…` | `TamilOnly` | Tamil |
| `Naan Suresh, phone 9003789456…` | `LatinOnly` | English (Tanglish) |
| `வாடிக்கையாளர் Ravi Kumar phone…` | `Mixed` | Both |
| `Callback on 9123456780…` | `NoLetters` | Neither (phone via Regex) |

---

## 8. Configuration and dependency injection

### `appsettings.json`

```json
{
  "PiiRedaction": {
    "OnnxModelPath": "models/ner-model.onnx",
    "EnglishOnnxModelPath": "models/en/ner-model.onnx",
    "TamilOnnxModelPath": "models/ta/model.onnx",
    "EnableTamilNer": true
  }
}
```

| Setting | Effect |
|---------|--------|
| `EnglishOnnxModelPath` | Primary English model |
| `OnnxModelPath` | Legacy English fallback |
| `TamilOnnxModelPath` | Tamil model |
| `EnableTamilNer` | `false` = English-only routing |

### DI registration

```csharp
services.AddSingleton<EnglishOnnxNerRunner>();
services.AddSingleton<TamilOnnxNerRunner>();
services.AddSingleton<IOnnxNerModelRunner, RoutingOnnxNerModelRunner>();
// OnnxNerPiiDetector receives IOnnxNerModelRunner (the router)
```

Same pattern in `PiiRedaction.ConsoleApp` and `PiiRedaction.TestHarness.Wpf` `ServiceCollectionExtensions.cs`.

Detector registration order in composite: **Domain → Regex → ONNX NER**.

---

## 9. Running and testing

### Build

```bash
dotnet restore
dotnet build
```

### Console app

```bash
# All 16 samples (English + Tamil/Tanglish/mixed)
dotnet run --project src/PiiRedaction.ConsoleApp

dotnet run --project src/PiiRedaction.ConsoleApp -- --list
dotnet run --project src/PiiRedaction.ConsoleApp -- --name TamilCustomerNameOnly
dotnet run --project src/PiiRedaction.ConsoleApp -- --interactive
```

Samples: `src/PiiRedaction.ConsoleApp/Samples/SamplePromptCatalog.cs`

### WPF test harness (Windows)

```bash
dotnet run --project src/PiiRedaction.TestHarness.Wpf
```

- **Category dropdown:** Career Guidance, Banking & Financial, Negative, Edge & Harness
- Click prompt → loads input; **Redact** runs pipeline
- **Run All** executes scenarios in the selected category
- Script badge shows predicted routing (`LatinOnly`, `TamilOnly`, `Mixed`)

### Download models

```powershell
.\scripts\download-ner-model.ps1
.\scripts\download-tamil-ner-model.ps1
```

If Tamil PowerShell download 404s, use Python 3.12+:

```powershell
.\scripts\download-tamil-ner-model.ps1 -Python "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe"
```

### Tests

```bash
dotnet test
dotnet test --filter "Category=RealModel"
dotnet test --filter "Category=TamilNer"
dotnet test --filter "FullyQualifiedName~ScriptRouterTests|FullyQualifiedName~RoutingOnnxNerModelRunnerTests"
```

Tests skip gracefully when ONNX files are absent.

### Console sample categories

| Category | Examples |
|----------|----------|
| NER (English) | `CustomerNameOnly`, `MrTitlePerson`, `TwoCustomersInOnePrompt` |
| NER (Tamil) | `TamilCustomerNameOnly`, `TamilFullFinancial` |
| Tanglish / Mixed | `TanglishCustomer`, `MixedTamilEnglish` |
| Regex / Domain | `AllRegexTypes`, `AllDomainIds` |
| Negative | `NoPiiCleanTicket` |

---

## 10. Tamil and Tanglish support

### Implementation status

| Phase | Status | Scope |
|-------|--------|-------|
| **1** Generic ONNX token classifier | Done | `OnnxTokenClassifierRunner`, encoders, `NerLabelConfig` |
| **2** Tamil download + config | Done | Scripts, dual paths, `EnableTamilNer` |
| **3** Script routing + DI | Done | `ScriptRouter`, `RoutingOnnxNerModelRunner` |
| **4** Tests, samples, docs | Partial | Tests/samples done; eval metrics open |
| **5** Optional enhancements | Not started | See below |

### Remaining gaps (Phase 4–5)

| Gap | Impact |
|-----|--------|
| Tamil numeral normalization (௦–௯ → 0–9) | May miss phone/Aadhaar in Tamil script |
| Tanglish heuristics (`peru`, `enga peru`) | Better Latin-name recall in Tamil context |
| Label-aware regex cues | Contextual name detection |
| Fail-closed when NER missing | Compliance hardening |
| MuRIL model swap | If Tamil recall insufficient |

### Tanglish expectations

| Input | Handler | Expected recall |
|-------|---------|-----------------|
| Tamil script names | Tamil ONNX | High (with tuning) |
| Latin Indian names (`Ravi Kumar`) | English ONNX | High |
| Tanglish spellings (`Senthil`) | English NER + optional heuristics | Medium |
| Code-mixed prompts | Both models + merge | Medium–high for IDs; names variable |

### Success metrics (eval set target)

| Metric | MVP target |
|--------|------------|
| Tamil script person recall | ≥ 85% |
| Tanglish person recall | ≥ 70% |
| False positives on clean prompts | ≤ 5% |
| Structured PII in Tamil prompts (regex) | ≥ 95% |
| English canonical regression | 100% |

---

## 11. Git remote setup (Xenovex)

Remote: `https://xts.xenovex.com/Bilal-Nazer-Ali/llm-pii-poc.git`

### Create and push

```powershell
cd C:\Users\bilal.n\Projects\llm-pii-poc
$git = "C:\Program Files\Git\bin\git.exe"

& $git remote add origin <YOUR_CLONE_URL>
& $git branch -M main
& $git push -u origin main
```

Use an **empty** remote repository (no README) when pushing existing history.

### Committed vs gitignored

| Committed | Gitignored |
|-----------|------------|
| `src/`, `tests/`, `scripts/`, `docs/` | `bin/`, `obj/`, `.vs/` |
| `README.md`, `PiiRedaction.slnx` | `models/*.onnx`, `vocab.txt`, `models/en/*`, `models/ta/*` |
| `models/en/.gitkeep`, `models/ta/.gitkeep` | `scratch/` |

After clone, run model download scripts locally.

---

## 12. Improvement roadmap

Post-POC items **not yet implemented**. Current maturity: strong architecture and tests; production needs fail-closed policy, API host, and observability.

### P0 — Security and correctness

| Item | Proposal |
|------|----------|
| Fail-closed when NER unavailable | `RequireNerOnStartup`, `BlockLlmWhenNerUnavailable` options |
| Outbound LLM guard | Verify sanitized text before `IChatClient` |
| Truncation warning | Surface 128-token limit in `SanitizationResult` |
| NER confidence | Populate `PiiEntity.Confidence` or hide UI column |
| WPF leak check | Use placeholder map, not naive `Contains` |

### P1 — Platform

| Item | Proposal |
|------|----------|
| `PiiRedaction.Composition` | Shared `AddPiiRedactionServices` (Console + WPF duplicate today) |
| Unified prompt catalog | Single source for console, WPF, golden tests |
| Async `IPromptSanitizer` | Replace WPF `Task.Run` wrapper |
| `PiiRedaction.Application` | Shared orchestration for API/WPF |
| Minimal API + health checks | `POST /v1/prompts/sanitize`, model readiness |
| Tamil Phase 4 | Numeral normalization, Tanglish heuristics |

### P2 — Operations

| Item | Proposal |
|------|----------|
| Placeholder audit store | TTL, encryption, correlation ID |
| Observability | Metrics, OpenTelemetry traces |
| ONNX session pool | Concurrency strategy for API load |
| CI pipeline | Fast tests without models; nightly real-model job |

### Suggested phases

1. **Production hardening** — fail-closed, composition root, API, truncation metadata (~1–2 weeks)
2. **Detection quality** — normalizer, Tamil Phase 4, regex hardening (~1 week)
3. **Operations** — audit store, metrics, session pool (~1–2 weeks)

---

## 13. Key source files

| Topic | Path |
|-------|------|
| Script classification | `src/PiiRedaction.Core/Detection/ScriptRouter.cs` |
| **Model branch decision** | `src/PiiRedaction.Infrastructure/Onnx/RoutingOnnxNerModelRunner.cs` |
| English NER | `src/PiiRedaction.Infrastructure/Onnx/EnglishOnnxNerRunner.cs` |
| Tamil NER | `src/PiiRedaction.Infrastructure/Onnx/TamilOnnxNerRunner.cs` |
| Shared ONNX inference | `src/PiiRedaction.Infrastructure/Onnx/OnnxTokenClassifierRunner.cs` |
| NER detector | `src/PiiRedaction.Core/Detection/OnnxNerPiiDetector.cs` |
| Sanitizer | `src/PiiRedaction.Core/Sanitization/PromptSanitizer.cs` |
| Composite merge | `src/PiiRedaction.Core/Detection/CompositePiiDetector.cs` |
| Options | `src/PiiRedaction.Core/Configuration/PiiRedactionOptions.cs` |
| DI | `src/PiiRedaction.ConsoleApp/DependencyInjection/ServiceCollectionExtensions.cs` |
| Console samples | `src/PiiRedaction.ConsoleApp/Samples/SamplePromptCatalog.cs` |
| WPF catalog | `src/PiiRedaction.TestHarness.Wpf/Services/TestPromptCatalog.cs` |
| Routing tests | `tests/PiiRedaction.Infrastructure.Tests/Onnx/RoutingOnnxNerModelRunnerTests.cs` |
| Script tests | `tests/PiiRedaction.Core.Tests/Detection/ScriptRouterTests.cs` |

---

*Last consolidated: July 2026. Replaces separate architecture, NER models, routing reference, Tamil plan, improvement roadmap, and Git setup documents.*