SmartDuke Technologies
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Solution·AI agents·FinTech

AI agents for FinTech.

Production-grade agents engineered for fintech and financial services.

In brief

SmartDuke builds ai agents for fintech and financial services — systems that autonomously complete multi-step workflows that previously required human orchestration. AI in financial services is high-stakes work — explainability, audit trails, and regulatory readiness are non-negotiable, and that's the bar we build to. Our approach: Eval coverage on every loop, observability into every tool call, and explicit guardrails around action surfaces before the agent ever touches production.

Why fintech and financial services are doing this now

The problems
we keep solving.

AI in financial services is high-stakes work — explainability, audit trails, and regulatory readiness are non-negotiable, and that's the bar we build to.

01 / 03

Regulatory compliance complexity grows quarterly

Every new regulation expands the surface area your compliance team has to monitor and document.

02 / 03

Manual KYC and underwriting are bottlenecks

Document review, identity verification, and credit assessment are document-heavy workflows that take hours per case.

03 / 03

Fraud detection at scale is a data problem

Rules engines flag too much; ML models flag too little; both miss novel fraud patterns.

Use cases

Three things we'd build
first.

Concrete starting points for ai agents in fintech and financial services. We pick the one with the highest leverage and the cleanest measurement story.

  1. Idea 01

    Compliance summarizer that ingests regulatory updates and flags impact on policies

  2. Idea 02

    KYC agent that processes identity documents and surfaces edge cases for human review

  3. Idea 03

    Fraud-detection copilot for analysts, with full case narrative and citations

Outcome metric → Time per case, false-positive rate, and audit-trail completeness
How we engineer it

Production-grade,
from day one.

We use planner-executor, ReAct, or supervisor-worker loops depending on the problem shape — and resist multi-agent orchestration when a single-agent loop solves it.

01 /04

Evals before launch.

Every loop, tool call, and structured output is graded with a frozen test set and an explicit rubric. Failed evals block the deploy.

02 /04

Telemetry from day one.

Traces, latency budgets, token costs, and error rates wired up before the first user touches the system.

03 /04

Guardrails as architecture.

Input validation, output verification, escape hatches, and human handoff paths designed in — not bolted on after incidents.

04 /04

Boring stack on the edges.

Cutting-edge model in the middle. Reliable infrastructure around it. Stability where it earns its place.

Common failure modes we engineer against
  • ×Runaway loops on ambiguous inputs
  • ×Tool-call failures invisible to standard APM
  • ×Context truncation as conversations grow
  • ×Hallucinated actions when grounding is weak
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FAQ · 04

Common questions.

01

How long does it take to build ai agents for FinTech?

Discovery is one week. A working prototype (Spark) is 2–3 weeks. Full production Build for fintech and financial services typically runs 8–12 weeks depending on data complexity, integrations, and compliance scope. We commit to a precise timeline at quote stage.

02

What does pricing for ai agents typically look like?

Every engagement is scoped to outcomes, not hours. Discovery starts in the low four figures. Spark and Build are priced per project. Embed retainers are monthly. We return a quote within 24 hours of inquiry.

03

Can you take over an existing agents project that's stalled?

Yes — it's a common engagement. We review what's there, tell you honestly what stays and what we'd rebuild, then ship it to production. FinTech engagements often start this way.

04

What's different about your approach to ai agents?

Eval coverage on every loop, observability into every tool call, and explicit guardrails around action surfaces before the agent ever touches production. We hold the same engineering bar across every engagement, regardless of industry — but the specifics for fintech and financial services are tuned to your trends and pain points.

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