QuantumLayer Platform
QuantumVerifi is built by QuantumLayer Platform Ltd — a London-based software company building infrastructure where AI agents design, build, validate, and operate software systems.
Our orchestration engine transforms natural language briefs into production-ready software through specialized agents, strict output contracts, and multi-layer verification. QuantumVerifi Scout is the quality engineering layer — the first product in a broader platform that will span architecture, deployment, operations, and visual intelligence.
Why we built Scout
Every AI code tool makes the same promise: “generate tests automatically.” We tried them all. The tests looked right but failed. Security reports had no fix code. Performance claims came with no execution proof.
So we built what we wanted: a platform where every test runs in an isolated sandbox, failures self-heal automatically, results come with cryptographic evidence, and — when you enable training — it improves as it learns your codebase patterns.
QuantumVerifi isn't another code generator. It's a 7-engine quality platform where the output is proof, not hope.
The 7 engines
Analysis Engine
Deep codebase understanding with multi-agent intelligence. 6 parallel agents analyze page semantics, authentication flows, form structures, business journeys, and accessibility — simultaneously. RAG context enriches each subsequent analysis.
Execution Engine
Tests don't just get generated — they run. 6 sandbox providers (AKS K8s Jobs, Modal, E2B, Docker, microVM, local) execute tests in isolated containers with language-specific images. Real compilation, real test frameworks, real results.
Self-Healing Engine
When tests fail, the Healer Agent clusters errors by type (undefined vars, missing imports, type errors, async issues) and regenerates with targeted fix strategies. Up to 3 healing cycles with few-shot learning from previous fixes.
Visual Intelligence
Predictive vision model (inspired by V-JEPA 2) detects UI regions (headers, forms, modals, navigation), identifies frameworks (React, Vue, Angular), scores element importance, and generates 1024-d visual embeddings for similarity matching.
Evidence Engine
SHA-256 evidence chains with canonical JSON serialization create tamper-evident audit trails. Each event links to the previous via prev_event_hash, enabling cryptographic verification for regulated industries.
Training Engine
QLoRA fine-tuning on your codebase patterns. Every analysis harvests training data — source code, generated tests, validation outcomes. This data trains per-tenant adapters that understand your coding conventions and domain logic.
Inference Engine
Per-tenant adapter routing serves your custom-trained model for test generation. The routing layer automatically selects between base models and your fine-tuned adapters based on operation type.
Technology
Temporal
Durable workflow execution with automatic retries and progress checkpointing.
Qdrant
Vector database for RAG context — each analysis enriches the knowledge base.
LiteLLM
Multi-provider LLM gateway with failover across Azure, Anthropic, and Ollama.
Modal + AKS
6 sandbox providers for isolated test execution across languages and frameworks.
Tree-sitter
Universal AST parsing for 165+ programming languages.
QLoRA
Parameter-efficient fine-tuning creates per-tenant adapters from analysis data.
Mission
Quality engineering should compound. Each analysis should make the next one better. The training flywheel — where every test generation, validation outcome, and self-healing cycle produces training data — is our competitive moat.
We're building the first quality platform that truly learns your codebase, not just your language.
Company
QuantumLayer Platform Ltd · 86-90 Paul Street, London EC2A 4NE · Company No. 16381947
Business inquiries: [email protected]
Enterprise sales: [email protected]