Platform/Alfred

Deterministic Financial Intelligence and Exception Investigation

Investigate reconciliation breaks, trace payment discrepancies, and query complex multi-rail ledger states using natural language backed by deterministic proof.

+2k
Finance teams using Alfred daily
Alfred Investigation Console
Why is there a $1,420 discrepancy in the European settlement batch?
OP
A

Root cause identified: 3 SEPA Instant transactions settled on Saturday with interchange deductions from the acquiring bank (Ref: BAI2-88219).

Proof Citation: pack_eu_9812 | Match confidence: 100% deterministic

Alfred Core Capabilities

Built to handle the complexity of modern fintech operations at scale.

Natural Language Querying

Finance and operations teams can instantly ask detailed questions across millions of transactions without complex database queries.

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Automated Break Root-Cause Analysis

Alfred analyzes timing variances, processor fee deductions, currency conversion spreads, and gateway metadata to explain breaks.

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Zero Hallucination Proof Citations

Every explanation emitted by Alfred references immutable proof objects, exact BAI2 bank record numbers, and raw gateway transaction identifiers.

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Deterministic Proof Indexes

Alfred queries strictly against deterministic reconciliation indexes and verified proof packs, never guessing balances.

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Deterministic Intelligence vs Legacy Rules Engines

Generic AI tools hallucinate numbers, while legacy rules engines break under high volume. Alfred queries verified deterministic proof records.

Legacy Rules EnginesAlfred Proof Intelligence
Matching logic
Static rules requiring manual configuration
Deterministic matching indexes backed by Proof Engine
Exception investigation
Every exception requires manual spreadsheet review
Automated root-cause analysis with raw feed citations
Data format handling
Fails on format variations or timing differences
Normalizes heterogeneous feeds into standardized schemas
Audit traceability
Fragmented notes and manual email logs
Cryptographic proof packs and line-item citations
Scale
Requires proportional operations headcount
Sub-200ms querying across millions of transactions

How Alfred Handles Exceptions

Reconciliation intelligence is about deterministic resolution. Your operations team reviews only what genuinely requires human confirmation.

Step 1

Mismatch detected

A transaction arrives with a discrepancy: amount, account identifier, or timestamp does not match the expected record.

Step 2

Alfred checks context

Alfred queries historical settlement patterns, related transactions, and source metadata to isolate the root cause.

Step 3

Deterministic verification

When deterministic proof rules confirm the match, the exception is resolved, logged with complete audit citations, and documented.

Step 4

Ambiguous case surfaced with context

For complex multi-rail breaks, Alfred surfaces the exception with direct line-item citations to raw bank and gateway feeds.

See Alfred in Action

Query
"Show me all failed transactions > $1000 from last week categorized by error code."

I found 12 failed transactions totaling $18,450. The primary cause was "Insufficient Funds".

Breakdown by Error

Insufficient Funds65%
Bank Decline25%
Suspected Fraud10%

Action Items

Alfred API

Programmatic Access to Intelligence

Embed Alfred's capabilities directly into your internal tools, Slack bots, or customer-facing dashboards.

Natural Language to SQL

Send raw text queries, get structured data back. No parsing required.

Role-Based Scope

API keys can be scoped to specific ledgers or data sensitivity levels.

Async Webhooks

Trigger complex analysis jobs and receive results via webhook.

bash
curl -X POST https://api.naya.finance/v1/alfred/query \
  -H "Authorization: Bearer sk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What is the total volume of international transactions in Q3?",
    "filters": '{
      "currency": ["USD", "EUR"],
      "status": "settled"
    },
    "output_format": "json"
  }'

# Response

{
  "data": '{
    "total_volume": 452900.50,
    "currency": "USD",
    "transaction_count": 1240
  },
  "confidence": 0.99
}

Interactive Alfred Demo

Test natural language queries and automated exception root-cause analysis.

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