First Overview: timveroAI - How We Cut Lending System Implementation from Months to Days

In this video Dmitriy walks through the Building Platform, explains the problem timveroAI was built to solve, and demos it live: two new features implemented, tested, and documented in under 10 minutes. Watch the video or read the full breakdown below.

A quick recap: what is timveroOS and the Building Platform?

Most lending software on the market is a pre-assembled application. It works well - until your business needs something the application wasn't designed in mind - niche products, your bespoke workflows, custom pricing logic: these are exactly the places where SaaS boxes limit you in.

timveroOS is different. At its core is what we call the Building Platform - a framework of composable primitives rather than a fixed application. Our clients use these building blocks to construct lending automations that precisely match their business, at the cost and speed of a regular SaaS deployment.

The Building Platform is organized in layers:

• Security & compliance foundation - role-based access, multi-factor authentication, full audit trail
• Entity layer - configurable participants (borrower, co-borrower, guarantor, company), assets (collateral, invoices), and containers (applications, loans, campaigns)
• State machine builder - custom statuses, manual actions, and automated events without BPMN spaghetti
• Service modules - credit framework, payment hub, product engine, documents & e-signature, notifications, workflow automation, BI & analytics

The result: clients can customize data models, business flows, underwriting algorithms, servicing logic, and integrations - without rebuilding from scratch.

The problem we set out to solve

The Building Platform gives clients enormous flexibility. But flexibility has a cost: someone has to configure it. Specifically:

• Business analysts must translate requirements into the language of our platform primitives
• Developers must understand how those primitives work and implement them correctly
• The two teams must stay in sync throughout the process

Until recently, getting a client up and running on timveroOS took 1-2 months on average, from initial analysis through go-live. We set a goal at the middle of last year: cut that by 10×.

Our goal: reduce implementation time 10× - from weeks to hours.

The question was how. And the answer turned out to be AI - not generic AI for vibe-coding with hallucinations, but AI that deeply understands the Building Platform.

What timveroAI is - and what it actually does

timveroAI is not a standalone product. It's a layer built into timveroOS - currently delivered as a plugin for Claude Code, with a roadmap toward a fully conversational, no-IDE setup process.

The plugin contains three core capabilities:

Requirements formalization

Product owners, business analysts, and engineers describe what they want to build - in plain language, in BPM diagrams, in bullet points, however they think. timveroAI translates that into structured requirements expressed in the language of our building blocks. It asks clarifying questions. It maps intent to primitives. It catches gaps before a single line of code is written.

Guided implementation

Once requirements are formalized and approved, timveroAI hands them to its implementation skill. This skill reads the current state of the codebase, identifies the right building blocks, writes the implementation, and runs quality assurance against the original requirements - autonomously.

Living documentation

After every change, timveroAI updates the project's AI Docs: a structured, always-current record of which processes are implemented, what statuses exist, how they connect, what the preconditions are. Any developer - or business analyst - joining the project mid-stream has full context instantly.

The demo: from description to working feature in 7 minutes

In the video, Dmitriy walks through a live example. Starting from a basic skeleton application - a few statuses, a few actions (Approve, Decline) - he asks timveroAI to add two things:

• A second approval step after the initial approval, with a hard scoring check before the final decision
• A Void action on applications, cascading to decline the associated borrower regardless of their current status

Here's what happened, in order:

Step 1 - Context analysis

The plugin's brainstorming skill reviewed the current system: existing statuses, action sequences, preconditions, and connected workflows. It surfaced what was already there - including a soft hit and hard hit scoring flow already connected to the state machine.

Step 2 - Clarifying questions

Rather than making assumptions, it asked: Should the hard scoring workflow remain as an auto-trigger? Should statuses be added to the application container, not just the borrower? Should the void cascade to decline the borrower regardless of their current status?

All good questions - and the answers shaped a much cleaner implementation than a naive read of the original request would have produced.

Step 3 - Implementation plan

timveroAI generated a detailed plan: what it would build, with which building blocks, in what order. Dmitriy reviewed it and approved.

Step 4 - Build & test

The implementation skill took over. It explored the Building Platform capabilities, identified the correct primitives, wrote the code, and ran QA against the formalized requirements - autonomously, orchestrating a team of sub-agents in parallel.

Step 5 - Verification

The local application was opened and tested manually. The Void action was there. Clicking it voided the application and declined the borrower. The second approval flow worked exactly as designed. Permissions were correctly scoped.

Total time from request to verified, working feature: under 10 minutes. Estimated equivalent manual effort: 2–4 hours of analyst + developer time.

What this enables for our clients

We tested timveroAI internally and with two clients. The consistent finding: development velocity increases approximately 10× for configuration-heavy work on the Building Platform.

More concretely, a client can now:

• Take one of our pre-built skeleton projects (Risk, Documents, Servicing, Offers - and growing), combine them, and have a working, customized lending system running in under a week
• Add or modify features through plain-language conversation rather than extensive specification documents
• Keep their entire team - including non-engineers - aligned on what's been built and why, through always-updated AI Docs

Where we're headed

What you see in this video is timveroAI in its current form: a plugin that lives in the IDE, primarily used by engineers and technical product owners. It's already producing 10× acceleration.

Our vision is further: a fully conversational interface - no IDE required - where a business leader describes what they want to build (through charts, plain language, BPM diagrams, Q&A sessions), and the system handles requirements, implementation, QA, and deployment. A running, customized lending system delivered as a conversation.

We think we're roughly six months from that. We'll keep showing our work along the way.

If you have questions about timveroAI, what we're building, or how it might apply to your lending stack - reach out. We're happy to go deeper on any of this.