braingency
What we build

What we build

Four products and platforms, built and running in production. Each one started as a specific business problem that existing software did not solve well enough.

01

Lending ERP & CRM platform

The full lending cycle in one system

A complete operating system for lending businesses — consumer credit, auto loans, leasing and mortgages. Rather than stitching together separate tools for origination, compliance and collections, the platform handles the entire loan lifecycle in a single, coherent system:

In production In production with clients in Latvia, Spain and the United Arab Emirates.

  1. 01

    Application intake

    Multi-channel capture of loan applications with configurable product rules

  2. 02

    Processing and scoring

    Automated underwriting workflows with ML-driven credit scoring trained on the lender's own portfolio data

  3. 03

    AML and compliance

    Screening, KYC/KYB integrations and audit trails built into the process

  4. 04

    Contract generation

    Automated document production and e-signature workflows

  5. 05

    Portfolio management

    Accounting, servicing, payment processing and reporting across the active loan book

  6. 06

    Collections

    Structured debt recovery workflows with case management

fig. 05 — the operator's view

On top of the operational layer, we analyse the full incoming data stream and build large-scale ML models that optimise the processes themselves — improving scoring accuracy, identifying risk patterns and automating decisions that previously required manual review.

02

Learning management platform

Education operations, fully automated

A platform for organisations that deliver structured education at scale. Course creators can publish courses, take payment, assign and review homework, and track learner progress — with the entire administrative process automated end to end.

The platform includes a gamification layer designed to improve completion rates and engagement, addressing the drop-off problem that affects most online learning products.

In production We developed a learning platform for Johns Hopkins University in the United States.

fig. 06 — the learner's week
03

AI assistant with built-in CRM

An AI chat agent that remembers the conversation

A deployable AI chat assistant that can be embedded on any website. Through the admin panel, the assistant's knowledge base is populated with information about the company it represents, so it answers from the business's actual documentation rather than generic responses.

Unlike a standalone chat widget, the assistant includes its own CRM: every conversation is stored with a summarised record of what the customer asked and what was resolved, giving the sales and support teams a searchable history of customer intent rather than a stream of disconnected chat logs.

fig. 07 — conversation in, record out
04

Verteo — property valuation for lenders

ML-based real estate price prediction

Verteo is our proprietary platform for analysing and forecasting real estate values. Built on our own machine learning model trained on real market data, it produces valuations for individual properties across the market.

The point of the model is decision support: Verteo exists to help lenders decide how much to lend. An accurate, current valuation of the collateral is what determines the right loan amount, and getting that number wrong in either direction is expensive — it either over-exposes the loan book or turns away sound business.

The immediate applications are in lending: automated collateral valuation for mortgage underwriting, and property-value inputs for credit scoring systems. Verteo connects directly to our lending platform, so a mortgage application can be scored against a current, model-driven valuation rather than a stale appraisal.

In production Live in Latvia and currently being extended to Spain.

verteo / valuation Illustrative data
Location
Rīga · Teika
Type
2-room flat
Area
54 m²
Built
1978
Floor
4 / 5
Model estimate

€97,400

90% range €92,500–€102,300

31 comparable sales

Local market index, €/m²

1700 1800 1900 2025 2026 2027 today 1804 €/m² 1869
Local market index, €/m²
Month€/m²90% range
2024-121719—
2025-031697—
2025-061729—
2025-091729—
2025-121759—
2026-031783—
2026-061775—
2026-091804—
2026-12 (forecast)18201788–1852
2027-03 (forecast)18361779–1893
2027-06 (forecast)18531770–1936
2027-09 (forecast)18691761–1977
fig. 08 — one property, one estimate, one market
05 Technology

Built to stay in production

Our systems are built primarily in Ruby on Rails, chosen for its suitability for complex business logic and long-lived production systems. We build and integrate REST APIs, banking and payment provider connections, KYC/KYB services, credit bureau and third-party data sources, and our own machine learning services.

  • Ruby on Rails
  • REST APIs
  • Banking integrations
  • Payment providers
  • KYC / KYB services
  • Credit bureaus
  • Third-party data sources
  • In-house ML services
  • N-01Banking integrations
  • N-02Payment providers
  • N-03Credit bureaus
core rails

Lending platform

One data model across the whole cycle

  • Application intake
  • Processing & scoring
  • AML & compliance
  • Contract generation
  • Portfolio management
  • Collections
  • N-04KYC / KYB services
  • N-05Third-party data
  • N-06In-house ML services
fig. 04 — integration map
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