Fintech AI infrastructure
March 2026

The AI brain
for regulated fintech

Voice, chat, and workflow agents that don't just answer — they finish the job, inside the systems banks actually run.

$510K
ARR
$1M+
Qualified pipeline
12x
Growth in 6 months
75%
Automation in prod
Raising $5M Seed at $30M cap
Confidential · Gen2B 2026
The execution gap
Gen2B · 02

In fintech, answering is easy.
Resolving is hard.

Financial institutions face three forces colliding at once — and that's what makes resolution structurally hard to automate.

High-volume work

Simple requests that bury human agents and never end.

  • L1 support
  • Account servicing
  • Payment reminders
  • Collections follow-up

Fragmented systems

Data and actions scattered across disconnected silos.

  • CRM (Salesforce, HubSpot)
  • Ticketing (Zendesk, Intercom)
  • Core banking & payments
  • Internal back-office tools

Regulatory constraints

Strict requirements that generic AI cannot meet.

  • Audit trail requirements
  • Controlled escalation paths
  • QA visibility & scoring
  • Air-gapped deployment
The consequence Low automation, high handling cost, poor QA coverage, and missed revenue from slow resolution.
The solution
Gen2B · 03

An AI brain that finishes the job.

Not a chatbot. Not a copilot. A system that listens, decides, acts inside your CRM and core banking, and learns from every resolution.

AI Brain Gen2B Listen Voice + Chat Decide Propose & ask Act Execute in CRM Learn Self-healing

Four moves. One loop.

  • 1
    Listen on every voice and chat channel — across customers and operators.
  • 2
    Decide — spot patterns no human has time to catch, propose what to try.
  • 3
    Act — execute inside CRM, core banking, ticketing on your approval.
  • 4
    Learn — every resolved ticket makes the system smarter tomorrow.

"Humans define goals and guardrails. Gen2B executes the workflows — at machine scale, under regulation."

Product architecture
Gen2B · 04

Agent-native platform for regulated ops

Three modules live in production today. Two more in alpha. Deployable anywhere your regulator requires.

Live

Gen2Chat

Omnichannel L1 automation across WhatsApp, web, in-app SDK.

Live

Gen2Agent

Real-time voice AI — talks, sells, executes in CRM.

Live

Gen2Call

Speech analysis, emotion detection, QA scoring at scale.

Live

Data & Report Agent

Natural language access to your knowledge base via RAG.

Live

Action Layer

Executes workflows across CRM, core banking, fintech APIs.

Beta

Soft Collection

Smart debt recovery with context retention & partial pay.

Cloud (SaaS)
Private cloud (VPC)
On-premise (Air-gapped) — fintech preferred
3–4 month deployment cycle today
The flywheel
Gen2B · 05

Every interaction trains the system

Each voice or chat interaction creates structured learning signals. Our moat grows with every ticket resolved.

Continuous improvement 1. Classify Intent & risk 2. Score QA checks 3. Label Success/fail 4. Route Edge → human 5. Improve Refine prompts 6. Learn High-ROI actions

The defensive moat

"Our moat is not conversation data. It is the combination of conversation, action, score, and outcome."

  • Structured signals. We store metadata of why a conversation succeeded — not just the text.
  • Self-healing. Edge cases routed to humans become autonomous resolutions next time.
  • Customer-owned data. We improve from workflow outcomes, not raw customer data.
Growth projection
Gen2B · 06

Accelerating scale & efficiency

As deployment time shrinks, growth compounds. Same engineering playbook as Stripe and Plaid.

2026
Validate
5–8
Clients
$1.5M
ARR
Onboarding
3–4 months · manual integration
2027
Expand
20–50
Clients
$10M
ARR
Onboarding
1–2 months · standard connectors
2028
Scale
300+
Clients
$112M
ARR
Onboarding
1 hour · self-service
$510K $1.5M $10M $112M Today 2026 2027 2028
~75x ARR growth driven by an engineering bet on deployment automation — not a sales bet.
Traction & metrics
Gen2B · 07

Early proof in production

Real revenue, real customers, real conversion. This is not a thesis — it's a working system.

Annual recurring revenue
$510K
Verified ARR from active contracts
Qualified pipeline
$1M+
Six post-pilot deals in conversion
Growth rate
12x
ARR growth in last 6 months
Automation rate
75–82%
Full automation in live environment
Gross margin
>70%
SaaS margins on deployed volume
Routing accuracy
99%
Formal protocol — NASDAQ-listed bank
BI Group
12hr → 24/7 support same team. Voice expansion at ~4x ACV.
Punto Pago
63% promise-to-pay rate on collections pilot. In conversion.
Kazakhtelecom
$650K+ pipeline post-pilot. Largest telco in Central Asia.
Demand is strongest where buyers need both automation and control.
Commercial strategy
Gen2B · 08

Enter with any product. Expand to the platform.

A single workflow becomes the wedge. The platform becomes the contract.

LAND · STAGE 1 Gen2Chat $80K Gen2Call $50K Gen2Agent $50K Soft Collection $60K Single workflow EXPAND · STAGE 2 $500K – $1M ACV Add capabilities Social media analytics Data agent (RAG) Action layer (CRM) Multi-product SCALE · STAGE 3 $1M+ INSTITUTION-WIDE ACV Cross-department workflows Central governance & audit Shared customer data context Closed-loop optimization The platform
ICP
Banks, neobanks, lenders with 50+ support agents
Initial SAM
~1,200 institutions × $500K ACV = ~$600M opportunity
Long-term TAM
Global expansion via Mercuryo flagship deployment
Competitive landscape
Gen2B · 09

Not a better helpdesk.
A structural shift.

Incumbents are built for general support. We're built for regulated execution. They can't follow us into the buyers we win.

Capability Gen2B Intercom Fin Zendesk AI
Core focus Regulated customer ops Horizontal AI customer service Broad support suite
AI resolution rate 75–85% in production 50–60% (self-reported) Not publicly disclosed
Pricing model $0 seats + usage-based Seats + $0.99/resolution Seats + add-ons
Deployment SaaS / VPC / On-prem / Air-gapped SaaS-first SaaS-first
Voice QA / speech Native built-in Not native core Add-on / modular

The structural difference: We're not claiming incumbents can't automate. We're claiming they are structurally worse aligned for regulated, high-automation customer operations — and switching architecture is harder than adding features.

Team & round
Gen2B · 10

Built for enterprise AI deployment

Product, AI, and deployment depth — paired with a focused US go-to-market motion.

Core team

  • AA
    Armen Atayan
    CEO & Founder
    Founder-led sales & product vision.
  • AD
    Akshin Dzhangirov
    Co-founder · Fintech
    Mercuryo co-founder. Fintech strategy & ecosystem.
  • BN
    Bakht Niyazov
    Co-founder · Growth
    CIS regional growth & operations expert.
  • DM
    Denis Malimonov
    Head of AI
    Built KZ leading STT/TTS (gov-deployed). Creator of IrbisGPT & HyGPT.
  • AB
    Andrey Beliaev
    CTO
    Built AI for nuclear-grade industrial monitoring. Enterprise architecture & security.
The ask
$5M
Round
Seed at $30M post-money cap
24+ months runway
Product & AI
34%
Workflow depth, voice, QA, controls
US GTM
27%
Founder-led US expansion & first hires
Deployment & CS
16%
Convert pilots faster, drive expansion
Security & legal
10%
Enterprise procurement & deployment
Infrastructure
8%
Model, cloud, monitoring, reliability
G&A
5%
Lean operating overhead
When you invest in Gen2B,
you invest in every fintech in your portfolio.