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Solutions · Financial Services

AI Employees for Financial Services.

Sonzai Labs builds and operates AI Employees for banks, wealth managers, and insurers — for lead qualification, advisor enablement, customer support, and compliance triage. Forward-deployed engineers from the team behind $70M+ AI value at DBS Bank and OCBC's first gen-AI rollout. Production-grade in 4–6 weeks; gets sharper every month.

DBS Bank·$70M+ in AI value
OCBC Bank·First gen-AI rollout
Sonzai Labs·Mind Layer runtime
Pocket Souls·Consumer AI

What we build

Five operating roles a financial services team can hand off.

01

Lead qualification & routing

Score and route inbound leads across digital channels in seconds. Pull product fit from your catalog, KYC posture from internal systems, and historical signals from your CRM. Hand a fully-briefed lead to the right RM or sales team — already enriched.

  • Multi-channel ingestion: web, app, branch referrals, partner feeds
  • Risk- and product-aware scoring against your taxonomy
  • CRM-native routing with audit-ready handoff notes
02

Relationship-manager enablement

An AI Employee that sits behind every RM, not in front of every customer. Pre-meeting briefs, portfolio commentary, regulatory-safe answers, and follow-up drafting — built on the customer context your RMs already have access to.

  • Pre-meeting client briefs from CRM + transactions + previous notes
  • Compliant draft messages with disclosure boilerplate built in
  • Personalized follow-ups that learn each RM's voice
03

Customer service triage

Before an agent picks up, the AI Employee has already pulled every relevant case, identified the product, surfaced the regulatory edge cases, and drafted three response paths. Faster handle time, fewer escalations, full audit trail of why each decision was made.

  • Multi-system case context (core banking, claims, ticketing) on first touch
  • Edge-case detection: vulnerable customer, complaint, regulator-flagged
  • Drafted responses with citations, never paraphrased policy
04

Compliance & risk triage

Inbound documents — KYC packs, dispute letters, regulatory queries — get parsed, classified, and routed with a structured summary. Humans approve every decision; the AI Employee just handles the reading and the first draft.

  • Document classification + structured extraction with confidence scores
  • Auto-flagging of clauses that historically triggered escalation
  • Audit log of every assertion the AI made and why
05

Back-office operations

Reconciliation exceptions, payment investigations, internal queue triage. The AI Employee runs the boring parts of operations 24/7 and only escalates when a human is genuinely required.

  • Pattern detection across high-volume, high-similarity work
  • Configurable escalation thresholds by risk and dollar amount
  • Human-in-the-loop on every irreversible action

How we build

Four stages. First production deployment in 4–6 weeks.

011–2 weeks

Discovery

We map the workflow, the systems, the failure modes, and the business outcome worth automating. We ask which decisions the regulator audits and which ones don't matter.

021–2 weeks

Architecture

We design the agent loop, the state model, the integrations, the human escalation paths, and the production guardrails. Output: a build plan and a model risk doc.

032–4 weeks

Build

Focused first version, validated on real production-shaped data behind a feature flag. We expand only where the data supports it — never speculative scope.

04Ongoing

Operate

Hosted on Sonzai or your VPC. Weekly tuning windows. Memory and personality compound, so the AI Employee gets sharper with every conversation, not staler.

Why financial services is different

Production-grade for regulators, not just for demos.

Audit trails by default

Every decision is logged with the inputs it saw, the prompt assembly, the model used, and the policy that constrained it.

On-prem and VPC deployment

Run inside your tenancy or ours. Memory and audit data can stay on your side; only inference traffic crosses the boundary.

Human-in-the-loop where it matters

Configurable approval gates on irreversible actions — you decide which thresholds escalate to a human.

Data residency in Southeast Asia

Deployments in Singapore, Indonesia, Malaysia, Philippines, Thailand, and Vietnam are in scope. We've shipped under MAS and OJK regimes.

Why ours compound · Multiplayer Memory

Compliance-grade memory.
Shared by every agent on the desk.

Wealth advisor, KYC analyst, fraud-triage specialist — every AI Employee on the project shares a typed knowledge graph. Decisions, account context, MAS-relevant policy, and customer history all live in the same store, with audit trail and source anchoring. Newer information supersedes older facts; nothing the desk learns goes back to zero.

  • Intra + inter-agent — same graph, all your agents share it
  • Typed facts (Person, Account, Decision, Promise, Document)
  • Documents auto-ingest; agents auto-update the KB
  • Newer information supersedes older facts, automatically
agents · users · documents · facts
session.End() · per-pair learning · evolution
Self-Learning Layer · why retention compounds

Sharper every quarter.
Without re-training a thing.

Every conversation ends with sessions.End() — kicking off fact extraction, dedup, personality drift, mood update, diary, and quality scoring. Per-(agent, customer) SGD and bandits tune retrieval to the way that specific account thinks. Day 1 is competent; Year 1 is a relationship the customer doesn't want to leave.

  • Per-(agent, user) retrieval tuned by SGD on each session's reward
  • Multi-armed bandit (Thompson sampling) over memory clusters
  • Shadow-rollout RL with auto-revert — production never sees a bad policy
  • Daily/weekly jobs: tree pruning, decay, diary, milestone detection
Per-(agent, user) sharpnesscompounding
Day 1
Week 1
Month 1
Year 1

Frequently asked

What financial services teams ask first.

Yes. Sonzai's runtime supports the audit trails, human-in-the-loop escalation, configurable PII redaction, and on-prem / VPC deployment options that MAS-regulated workflows require. The team has shipped production AI inside DBS Bank and OCBC under exactly these constraints — we know what survives a model risk review and what does not.

Have us build your AI Employee.

Free 30-minute consultation with the founders. We'll scope the workflow, the systems, and the regulatory edge — and tell you honestly whether managed build is the right path.

Have us build yours →