# hncb-fusion-deid-demo

Demo of the HNCB use case: a **reversible PII de-identification round trip**
through **Axway Amplify AI Gateway (Fusion)**, with the reasoning done by an
**Amazon Bedrock AgentCore** agent. The advisor types a query containing a real
name; the cloud only ever sees a token; the real identity is restored before the
answer is shown.

> **Working with Claude Code? Read `CLAUDE.md` first** — it has the context,
> commands, and task backlog.

> **Status: unrun scaffold.** Authored, not executed. Review everything, pin
> dependency versions, and adjust AgentCore specifics to the current CLI.
> Demo-grade, not production-grade.

## Fusion is shared SaaS
Fusion is **not deployed by this repo** — it's a shared Amplify AI Gateway SaaS
instance, configured in its console (`fusion/POLICY_SETUP.md`). Because it's SaaS,
anything it calls must be a **public HTTPS endpoint with auth**. So the AWS side's
job is to expose two endpoints Fusion calls — **`/tokenize`** (ingress) and
**`/restore`** (egress) — plus host the detector, vault, RAG tool, and agent.
Those two endpoints are the main remaining build (tasks T1/T2 in `CLAUDE.md`).

## What it demonstrates
Raw PII (a Chinese name + a Taiwan ROC ID) is detected on ingress, replaced with a
**random, format-safe token**, and only the tokenized prompt goes to the cloud
agent. The agent tool-calls back "on-prem" with the token, gets a de-identified
evidence package, and writes talking points. Fusion restores the identity on the
way out. **The money shot:** show the Bedrock request / AgentCore trace live — the
cloud only ever saw `CUST_000123`, never `王小明`.

## Trust zones are logical
Everything is one AWS account. The "on-prem" zone is tag-labelled resources
(`Zone = on-prem-VPC-A`) standing in for HNCB's branch data centre. Proves
data-flow behaviour, not physical residency — say so on camera.

## Component → service map (their 8 steps)
| Step | Component | Service in this repo |
|---|---|---|
| 1, 8 | Advisor UI | `ui/index.html` on S3+CloudFront (or local) |
| 2, 3-route, 8 | **Fusion AI Gateway** (the product) | **shared SaaS** — configured via `fusion/POLICY_SETUP.md` (not deployed) |
| 2 (ingress), 8 (egress) | `/tokenize` + `/restore` endpoints Fusion calls | **TODO** `gateway_api/` (tasks T1/T2) |
| 2 | PII **detector** (typed findings, not redaction) | Presidio on Fargate — `presidio/` |
| 2, 4, 8 | Token **vault** (reversible map) | DynamoDB — `terraform/main.tf` |
| 3, 7 | Cloud **agent** + model | AgentCore Runtime + Bedrock — `agent/` |
| 4 | Tool bridge (Lambda → MCP tool) | AgentCore Gateway — `scripts/agentcore_setup.sh` |
| 4-6 | On-prem **RAG tool** + data | Lambda + DynamoDB — `lambda_rag/`, `seed/` |
| all | Observability | AgentCore Observability + CloudWatch |

## Repo layout
```
CLAUDE.md            start here if using Claude Code (context + task backlog)
terraform/           DynamoDB (vault + customers), RAG Lambda, IAM, Presidio hosting
lambda_rag/          RAG tool: token resolve -> de-identified evidence package
gateway_api/         TODO: /tokenize + /restore endpoints Fusion SaaS calls (T1/T2)
agent/               Strands agent for AgentCore Runtime + tool schema
presidio/            PII detector service (typed findings) + Dockerfile
seed/                fake customer (Wang Xiaoming) + seed script
ui/                  advisor UI (restored-vs-tokenized split view)
scripts/             deploy.sh, agentcore_setup.sh, teardown.sh
fusion/              POLICY_SETUP.md (SaaS console config — the manual part)
```

## Prerequisites
`aws-cli` configured (creds + region), `terraform >= 1.5`, `docker`, `python3`,
the AgentCore CLI (`npm i -g @aws/agentcore`), Bedrock model access enabled for
`bedrock_model_id`, and access to the shared **Fusion SaaS** instance.

## Deploy
```bash
bash scripts/deploy.sh          # infra -> presidio image -> ECS -> seed -> AgentCore
# then: build /tokenize + /restore (gateway_api/, tasks T1/T2)
# then: configure the shared Fusion SaaS instance (fusion/POLICY_SETUP.md)
# then: point ui/index.html GATEWAY_URL at the Fusion SaaS entrypoint and open it
```

## Demo script (maps to the 8 steps)
1. Advisor UI: submit *"請幫我整理王小明最近三個月的理財往來，並給我下次拜訪話術。"*
2. Fusion (via `/tokenize`) detects `王小明` + `A123456789`, tokenizes, logs tokens only.
3. Show the Bedrock/AgentCore trace — the prompt the cloud saw contains `CUST_000123`.
4-6. Agent tool-calls back on-prem; RAG resolves the token, returns a summary.
7. Agent writes talking points (no PII).
8. Fusion (via `/restore`) restores `王小明`; the UI shows restored beside tokenized.

## Teardown
```bash
bash scripts/teardown.sh        # stop paying for Fargate / AgentCore
```

## Honest caveats
- **zh-TW detection is demo-narrow** — tuned to the scripted entities, not
  production recall. That remains the real-engagement risk.
- **Per-request randomization** lives in the `/tokenize` mint step; confirm it
  satisfies HNCB's "different each time" requirement.
- **The agentic token-resolution loop** (agent tool call → on-prem RAG resolves the
  token) is custom orchestration by design — where Fusion's depth is the argument.