Your LOS / Document Store
          │
          │  read-only connector
          ▼
  ┌───────────────────────────────────────────┐
  │           Vecminds Intelligence              │
  │                                           │
  │  Document Parser  ──►  Income Engine      │
  │  PDF · scan · CSV      gross · net ·      │
  │                        multi-source       │
  │                             │             │
  │                             ▼             │
  │              Discrepancy Detector         │
  │              cross-doc reconciliation     │
  │                             │             │
  │                             ▼             │
  │              Fraud Signal Model           │
  │              outcome-trained on your      │
  │              portfolio                    │
  │                             │             │
  │                             ▼             │
  │              Audit Logger (immutable)     │
  └─────────────────────────────┬─────────────┘
                                │  structured JSON
                                ▼
                    Your Underwriting UI
                                │
                                │  outcome tag (on close / default)
                                ▼
                    Outcome Flywheel
                    (retrains on your portfolio —
                    proprietary signal)

POST /v1/intelligence/verify
Authorization: Bearer ok_live_xxxxxxxxxxxxxxxxxxxx
Content-Type: application/json

# Node.js / TypeScript
npm install @vecminds/intelligence

# Python
pip install vecminds-intelligence

# Java (Maven)
# groupId: ai.vecminds  artifactId: intelligence-sdk  version: 2.4.0

# .NET
dotnet add package Vecminds.Intelligence

import { VecmindsClient } from "@vecminds/intelligence";

const client = new VecmindsClient({
  apiKey: process.env.VECMINDS_API_KEY,         // ok_live_...
  // baseUrl: "https://vecminds.your-vpc.internal/v1",  // VPC / on-prem
});

// This file runs on the server only. The VECMINDS_API_KEY env var
// is never bundled into the browser.
import { VecmindsClient } from "@vecminds/intelligence";
import { NextRequest, NextResponse } from "next/server";

const vecminds = new VecmindsClient({ apiKey: process.env.VECMINDS_API_KEY! });

export async function POST(req: NextRequest) {
  // 1. Authenticate the incoming request with your own session/auth
  const session = await getSession(req);
  if (!session) return NextResponse.json({ error: "Unauthorized" }, { status: 401 });

  // 2. Parse the multipart form submitted by your origination UI
  const form = await req.formData();
  const applicationId = form.get("application_id") as string;
  const files = form.getAll("documents") as File[];

  // 3. Forward to Vecminds server-to-server (key stays on the server)
  const job = await vecminds.verify.create({
    subject:   { id: applicationId, type: "loan_application" },
    documents: await Promise.all(
      files.map(async (f) => ({ name: f.name, data: Buffer.from(await f.arrayBuffer()) }))
    ),
    policy: "income.verify-2024",
    notify: "https://your-los.internal/webhooks/vecminds",
  });

  // 4. Return only the job ID to the browser — no key, no raw docs
  return NextResponse.json({ jobId: job.id });
}

// The browser never touches Vecminds directly.
// It uploads to YOUR route and receives only the job ID.
async function submitApplication(applicationId: string, files: File[]) {
  const form = new FormData();
  form.append("application_id", applicationId);
  files.forEach((f) => form.append("documents", f));

  const res = await fetch("/api/verify", { method: "POST", body: form });
  const { jobId } = await res.json();
  return jobId;  // poll /api/verify/[jobId] or wait for a push notification
}

// Receive via webhook (recommended) or poll:
const result = await client.verify.get(job.id);

// Verified income
console.log(result.income.gross_annual);   // 84200
console.log(result.income.sources);
// [{ type: "employment", employer: "Meridian Corp",
//    gross_annual: 84200, confidence: 0.97,
//    verified_from: ["pay_stub_aug.pdf", "bank_stmt_q3.pdf"] }]

// Discrepancies between documents
console.log(result.discrepancies);
// [{ field: "monthly_income",
//    document_a: { file: "pay_stub_aug.pdf", value: 7017, line: "Gross Pay" },
//    document_b: { file: "bank_stmt_q3.pdf", value: 6100, line: "ACH deposit avg" },
//    delta_pct: 0.15, severity: "medium" }]

// Fraud signals (empty = clean)
console.log(result.fraud_signals);   // []
console.log(result.audit_id);        // "aud_3F8C1B"

// Called by your LOS webhook / internal event bus when a loan closes.
// This is server-only code — a browser session is never involved.
async function onLoanClosed(event: LoanClosedEvent) {
  const jobId = await db.getVecmindsJobId(event.applicationId);

  await vecminds.outcomes.tag({
    job_id:            jobId,
    outcome:           "repaid",   // repaid | default | early_payoff | charged_off
    months_to_outcome: event.monthsFromOrigination,
    loan_amount:       event.loanAmount,
    product_type:      "personal",
  });
}

{
  "job_id":              "job_9A4D2E",
  "status":              "completed",
  "processing_time_ms":  2100,
  "income": {
    "gross_annual":  84200,
    "net_monthly":   5616,
    "confidence":    0.97,
    "sources": [{
      "type":         "employment",
      "employer":     "Meridian Corp",
      "gross_annual": 84200,
      "pay_frequency":"biweekly",
      "verified_from":["pay_stub_aug.pdf", "bank_stmt_q3.pdf"],
      "confidence":   0.97
    }]
  },
  "discrepancies": [{
    "field":      "monthly_income",
    "document_a": { "file": "pay_stub_aug.pdf", "value": 7017, "line": "Gross Pay" },
    "document_b": { "file": "bank_stmt_q3.pdf", "value": 6100, "line": "ACH deposit avg" },
    "delta_pct":  0.15,
    "severity":   "medium",
    "note":       "Pay stub reflects pre-tax gross; bank deposits reflect net-of-deductions ACH."
  }],
  "fraud_signals":    [],
  "audit_id":         "aud_3F8C1B",
  "policy_version":   "income.verify-2024@v3"
}

{
  "subject":   { "id": "app_7C3B1", "type": "loan_application" },
  "documents": [
    { "name": "pay_stub_aug.pdf", "data": "<base64>" },
    { "name": "bank_stmt_q3.pdf", "url":  "https://your-bucket.s3.amazonaws.com/bank_stmt_q3.pdf?..." },
    { "name": "1040_2023.pdf",    "data": "<base64>" }
  ],
  "policy":   "income.verify-2024",
  "notify":   "https://your-los.internal/webhooks/vecminds",
  "metadata": { "loan_officer_id": "lo_882", "product": "personal_unsecured" }
}

{
  "job_id":                  "job_9A4D2E",
  "status":                  "processing",
  "created_at":              "2024-08-14T14:22:31Z",
  "estimated_completion_ms": 2500
}

{
  "job_id":             "job_9A4D2E",
  "status":             "completed",
  "processing_time_ms": 2100,
  "income": {
    "gross_annual": 84200,
    "net_monthly":  5616,
    "confidence":   0.97,
    "sources": [{
      "type":         "employment",
      "employer":     "Meridian Corp",
      "gross_annual": 84200,
      "verified_from":["pay_stub_aug.pdf", "bank_stmt_q3.pdf"],
      "confidence":   0.97
    }]
  },
  "discrepancies": [{
    "field":      "monthly_income",
    "document_a": { "file": "pay_stub_aug.pdf", "value": 7017, "line": "Gross Pay" },
    "document_b": { "file": "bank_stmt_q3.pdf", "value": 6100, "line": "ACH deposit avg" },
    "delta_pct":  0.15,
    "severity":   "medium",
    "note":       "Pay stub reflects pre-tax gross; bank deposits reflect net-of-deductions ACH."
  }],
  "fraud_signals":  [],
  "audit_id":       "aud_3F8C1B",
  "policy_version": "income.verify-2024@v3"
}

{
  "audit_id":    "aud_3F8C1B",
  "job_id":      "job_9A4D2E",
  "subject_id":  "app_7C3B1",
  "policy_version": "income.verify-2024@v3",
  "created_at":  "2024-08-14T14:22:31Z",
  "completed_at":"2024-08-14T14:22:33Z",
  "events": [
    { "ts": "2024-08-14T14:22:31.012Z", "type": "document_received",
      "file": "pay_stub_aug.pdf", "size_bytes": 184320 },
    { "ts": "2024-08-14T14:22:31.420Z", "type": "income_extracted",
      "file": "pay_stub_aug.pdf", "field": "gross_monthly",
      "value": 7017, "page": 1,
      "bounding_box": { "x": 0.62, "y": 0.34, "w": 0.18, "h": 0.04 } },
    { "ts": "2024-08-14T14:22:32.100Z", "type": "discrepancy_raised",
      "field": "monthly_income", "delta_pct": 0.15, "severity": "medium" },
    { "ts": "2024-08-14T14:22:33.100Z", "type": "job_completed" }
  ]
}

# vecminds-connector.yaml
connector: encompass
auth:
  client_id:     $ENCOMPASS_CLIENT_ID
  client_secret: $ENCOMPASS_CLIENT_SECRET
  instance_id:   $ENCOMPASS_INSTANCE_ID

trigger:
  event:     milestone_change
  milestone: "Loan Submitted"

document_mapping:
  - efolder_name: "Pay Stubs"
    vecminds_type:   pay_stub
  - efolder_name: "Bank Statements"
    vecminds_type:   bank_statement
  - efolder_name: "Tax Returns"
    vecminds_type:   tax_return

vecminds:
  api_key: $VECMINDS_API_KEY
  policy:  income.verify-2024
  notify:  https://your-los.internal/webhooks/vecminds
  metadata:
    loan_officer_id: $ENCOMPASS_LOAN_OFFICER_ID

{
  "event":      "verification.completed",
  "job_id":     "job_9A4D2E",
  "subject_id": "app_7C3B1",
  "timestamp":  "2024-08-14T14:22:33Z",
  "data": { /* full verified credit file */ },
  "metadata":   { "loan_officer_id": "lo_882" }
}

import crypto from "crypto";

function verifyWebhook(payload: string, signature: string, secret: string): boolean {
  const expected = "sha256=" + crypto
    .createHmac("sha256", secret)
    .update(payload, "utf8")
    .digest("hex");
  return crypto.timingSafeEqual(Buffer.from(signature), Buffer.from(expected));
}

app.post("/webhooks/vecminds", (req, res) => {
  const sig = req.headers["x-vecminds-signature"] as string;
  if (!verifyWebhook(req.rawBody, sig, process.env.VECMINDS_WEBHOOK_SECRET!)) {
    return res.status(401).send("Invalid signature");
  }
  const { event, data } = req.body;
  if (event === "verification.completed") {
    // hand data (verified credit file) to your underwriting UI
  }
  res.status(200).send("OK");
});

policy:       income.verify-custom
version:      "2024-02"
description:  "Employment income + fraud detection for prime personal loans"

income_sources:
  employment:
    weight:             1.0
    required_documents: [pay_stub, w2]
  self_employment:
    weight:             0.85
    required_documents: [1040, bank_statement]
  rental:
    weight:             0.75
    required_documents: [lease, bank_statement]

discrepancy:
  tolerance:   0.05          # 5% variance allowed before a discrepancy is raised
  severity_thresholds:
    low:    0.05             # 5–10% delta
    medium: 0.10             # 10–25% delta
    high:   0.25             # >25% delta
  auto_explain: true         # attach a natural-language note to each discrepancy

fraud:
  enabled:         true
  signals:         [metadata, formatting, internal_consistency, behavioral]
  block_on_signal: false     # raise signal but do not block — underwriter reviews

output:
  include_source_citations:  true
  include_confidence_scores: true
  include_bounding_boxes:    false   # true = PDF highlight overlay in your UI
  audit_retention_years:     7

import { VecmindsClient } from "@vecminds/intelligence";

const client = new VecmindsClient({ apiKey: process.env.VECMINDS_API_KEY });

// Submit and wait (sync mode)
const result = await client.verify.create({
  subject:   { id: "app_001", type: "loan_application" },
  documents: [{ name: "pay_stub.pdf", data: buffer }],
  policy:    "income.verify-2024",
  mode:      "sync",
});

// Tag outcome
await client.outcomes.tag({
  job_id:            result.job_id,
  outcome:           "repaid",
  months_to_outcome: 36,
});

// Fetch audit trail
const audit = await client.audit.get(result.audit_id);

from vecminds import VecmindsClient
import os

client = VecmindsClient(api_key=os.environ["VECMINDS_API_KEY"])

with open("pay_stub_aug.pdf", "rb") as f:
    job = client.verify.create(
        subject   = {"id": "app_001", "type": "loan_application"},
        documents = [{"name": "pay_stub_aug.pdf", "data": f.read()}],
        policy    = "income.verify-2024",
    )

# Poll for result (or use notify= for webhook)
result = client.verify.wait(job.id, timeout=30)

print(result.income.gross_annual)   # 84200
print(result.discrepancies)         # [...]

# Tag outcome
client.outcomes.tag(job_id=job.id, outcome="repaid", months_to_outcome=24)