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Enterprise software & LLM engineering

WaveDop

Intelligence that speaks the language of your business

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Three disciplines, one team

From the compute core to the user interface — with no hand-offs between contractors.

  • 01

    LLM Engineering

    Deploying and adapting LLMs to enterprise workflows: RAG pipelines, autonomous agents and AI assistants for your teams — delivered turnkey.

    RAG · Agents · Fine-tuning

  • 02

    Web Development

    Enterprise platforms, internal tools and integrations with the systems you already run — from architecture to production.

    Platforms · API · Integrations

  • 03

    Systems Software C++ / Python

    High-performance backends and compute cores where every microsecond counts: data streams, numerical models and integrations.

    C++ · Concurrency

Four stages, no surprises at the finish line

Every stage ends with a concrete deliverable you can verify.

  1. 01 / Diagnose

    Discovery

    We examine your processes, data and constraints. The result: a technical assessment and a defined project scope.

  2. 02 / Design

    Architecture

    We design the system: data models, service boundaries and load requirements.

  3. 03 / Build

    Development

    Iterative delivery with early demos of working components.

  4. 04 / Run

    Deployment & Support

    Launch in your environment, monitoring and continued development of the system.

  • <200ms

    Target retrieval latency in RAG search

  • 99.9%

    Target SLA for supported systems

  • 24/7

    Production system monitoring

  • 6–10 wks

    Typical launch of an LLM assistant for a support team

Tools we trust in production

LLM / AI
  • PyTorch
  • Transformers
  • CUDA
  • Vector DB
Backend
  • C++
  • Python
  • FastAPI
  • gRPC
Frontend
  • React
  • TypeScript
  • WebGL
  • Design Systems
Infra
  • Kubernetes
  • Docker
  • PostgreSQL
  • Redis

Let’s discuss your project

Describe your challenge and we’ll get back to you with a timeline and approach within two business days.

  • Mon–Fri, 10:00–19:00
  • Enterprise clients, NDA on request

WaveDop Ltd

Discuss a project
WAVEDOP — ENTERPRISE SOFTWARE & LLM ENGINEERING

From raw signal to working intelligence

We design and deploy LLM systems, web platforms and high-load C++ and Python software for large organizations — where an architectural mistake costs months and millions.

Discuss a project How we work
RAW.SIGNAL — C++ / PYTHON STRUCTURED.INTELLIGENCE — LLM
C++PythonPyTorchCUDATransformersFastAPIgRPCPostgreSQLKubernetesRedisReactDocker C++PythonPyTorchCUDATransformersFastAPIgRPCPostgreSQLKubernetesRedisReactDocker
§01 — SERVICES

Three disciplines, one engineering culture

From the compute core to the user interface — with no hand-offs of responsibility between contractors.

SVC.LLM — 01
LLM Engineering

Deploying and adapting large language models to enterprise workflows: RAG pipelines, autonomous agents, cost and latency control in production.

RAGAgentsFine-tuningInference
SVC.WEB — 02
Web Development

Enterprise platforms, internal tools and integrations with the systems you already run — from architecture to production.

PlatformsAPIIntegrations
SVC.SYS — 03
Systems Software C++ / Python

High-performance backends and compute cores where every microsecond counts: data stream processing, numerical models and hardware integrations.

C++ConcurrencyOptimization
§02 — PROCESS

Four stages, no surprises at the finish line

Every stage ends with a concrete deliverable you can verify.

01 / Diagnose
Discovery

We examine your processes, data and constraints. The result: a technical assessment and a defined project scope.

02 / Design
Architecture

We design the system: data models, service boundaries and load requirements.

03 / Build
Development

Iterative delivery with early demos of working components.

04 / Run
Deployment & Support

Launch in your environment, monitoring and continued development of the system.

§03 — TARGETS

What we keep under control

<200ms
Target retrieval latency in RAG search
99.9%
Target SLA for supported systems
24/7
Production system monitoring
6–10 wks
Typical launch of an LLM assistant for a support team
§04 — STACK

Tools we trust in production

LLM / AI
PyTorch
Transformers
CUDA
Vector DB
BACKEND
C++
Python
FastAPI
gRPC
FRONTEND
React
TypeScript
WebGL
Design Systems
INFRA
Kubernetes
Docker
PostgreSQL
Redis
§05 — CONTACT

Let’s start by assessing your challenge

Let’s discuss your project

Describe your challenge and we’ll get back to you with a timeline and approach within two business days.

Mon–Fri, 10:00–19:00
We work with large and enterprise clients