AI that works with your data and systems

We design and deliver AI-powered solutions: AI assistants, chatbots, analysts and autonomous agents that draw on your company’s knowledge, integrate with your systems and meet your data protection requirements.

RAG
Vector Search
MCP
AI Agents
Multi-Agent Systems
Agent Harness
Self-hosted LLM

Discuss your project See case studies

Since 2003
Clients in the EU, US and Ukraine
Your data stays under your control

What we build

Solutions that take routine work off your team and give instant access to your company’s knowledge.

Enterprise AI assistants

Your people stop spending hours searching for information. The assistant answers instantly from your policies, contracts, wiki and knowledge base, cites the source and respects access permissions.

RAG
Hybrid Search
Reranking
Knowledge Base
Citations

AI chatbots for customers

They advise on products, take requests and resolve routine enquiries around the clock on your website and in messaging apps. They remember customer context and hand complex cases over to a human agent.

Conversational AI
Long-term Memory
Human Handoff
Telegram
WhatsApp
Viber

AI analysts

They pull data from multiple systems, answer questions in plain language and produce reports with conclusions, charts and an explanation of what changed and why.

Text-to-SQL
Semantic Layer
AI BI Copilot
Anomaly Detection
Auto-reporting

Document processing

They read scans, extract data from contracts, invoices and applications, classify documents and pass the results to your accounting and business systems.

Document Intelligence
OCR
Information Extraction
Classification
PII Redaction

AI agents for business processes

They handle multi-step tasks end to end: process a request, gather data from several systems, update the CRM and prepare the result for human approval.

Agentic Workflows
Tool Calling
MCP
Human-in-the-loop
Multi-Agent Orchestration

Confidential AI

For companies that cannot send data outside: models run in your infrastructure, and documents are anonymised before processing.

Self-hosted LLM
On-premise
Private Cloud
Data Anonymisation
GDPR

We also build

Sales assistants — commercial proposals, call summaries, CRM updates.Sales Copilot · Call Summarization
Recruiting assistants — CV screening, candidate shortlisting, interview scheduling.AI Screening · Candidate Matching
Voice AI agents — answering calls, booking appointments, handling common questions.Voice AI · Speech-to-Text · Text-to-Speech
AI inside your product — smart search, personalised recommendations and a built-in assistant for your users.Semantic Search · Recommendations · In-app Copilot
AI in mobile apps — image and text recognition from the camera, offline operation.On-device AI · Core ML · ML Kit
AI for device data — analysing sensor and equipment readings, detecting anomalies, predicting failures.IoT Analytics · Predictive Maintenance
AI moderation — screening user-generated content and incoming requests.Content Moderation · Risk Scoring

Technical expertise

We cover the full modern AI engineering stack, from knowledge retrieval to autonomous agents and safety.

Knowledge and search

RAG (Retrieval-Augmented Generation): Gives AI access to your company data: documents, knowledge bases, spreadsheets, diagrams and scans. Employees and customers get accurate answers with links to the sources.
Advanced RAG, Agentic RAG and GraphRAG: Answer complex questions about relationships between customers, contracts and products, where a single document match is not enough.
Vector search: Finds information by the meaning of the query. Your team gets the data it needs faster, even without knowing the exact wording.
Hybrid search and reranking: Combine search by meaning with search by exact names, codes and SKUs, and bring the most relevant results to the top.
Embeddings and vector databases: Store the meaning of texts as vectors, with strong multilingual support: PostgreSQL + pgvector, Qdrant, Elasticsearch.
Document Intelligence: Reads scans, parses document structure and extracts data from tables and forms.

Agents and orchestration

AI agents: Complete multi-step tasks end to end: process requests, prepare documents and update data across systems.
Agent harness: Defines the agent’s tools, access rights, limits and checks, and logs every action it takes. Your business automates routine work reliably and predictably.
Context engineering: Gives the agent exactly the knowledge, rules and data the task requires. Answers are more accurate and costs are lower.
MCP (Model Context Protocol): Connects AI to your CRM, ERP, databases and other business services through an open standard. Integrations launch faster and solutions scale more easily.
Multi-agent systems: Split a complex process between specialised agents: planner, executor and reviewer. This automates processes that are beyond the capabilities of a single agent.
A2A (Agent-to-Agent): Brings agents from different platforms and vendors together in one process.
Human-in-the-loop: Routes critical decisions to a person for approval.
Computer-use agents: Operate applications that have no API through their user interface, just as a person would.

Models and infrastructure

LLM gateway and model routing: Send each task to the model with the best price-to-quality ratio and provide failover between providers.
Self-hosted models: Run on your servers or in a private cloud (vLLM, Ollama, GPU servers). Costs and data stay under your control.
Fine-tuning (LoRA): Adapts a model to your domain and terminology.
Structured outputs and function calling: Let AI return data in a strict format that your systems process automatically.
Cost optimisation: Prompt caching, context management and response caching reduce the cost of every request.

Quality, safety and LLMOps

Evals: Test AI quality on real-world scenarios before every release, including with LLM-as-a-judge.
Observability: Shows accuracy, agent actions, latency and cost in real time. Issues are caught early.
Guardrails: Protect against prompt injection, confidential data leaks and unwanted AI actions. Your company adopts new capabilities without unnecessary security or reputational risk.
PII detection and redaction: Automatically find and mask personal data.
AI governance: Ensures compliance with GDPR and the EU AI Act, with an audit trail of AI actions.

Stack: OpenAI · Anthropic Claude · Google Gemini · Gemma · Llama · Mistral · vLLM · Ollama · LangGraph · PostgreSQL + pgvector · Qdrant · Docling · Node.js · TypeScript · Python · Docker · Google Cloud

Case studies

Real projects where we proved the approaches we offer to our clients.

Internal R&D project

Safe AI processing of confidential contracts

Challenge: Use powerful cloud AI models on legal documents without sharing personal or commercial data with third-party services.
Solution: A Word document anonymisation tool with hybrid entity recognition. Rules detect bank details, IBANs, company registration numbers, phone numbers and emails. A local LLM adds names, company names and addresses. Detected data is replaced with typed placeholders and restored after the document has been processed.
Result: The document can be processed by any AI service while sensitive data stays inside the company. A person reviews every replacement, and the original is restored exactly.

PII Redaction
Reversible Pseudonymisation
Hybrid NER
Gemma
vLLM
Google Cloud GPU
Human-in-the-loop

Our own product — FINANCES & ACCOUNTING

AI support for an accounting system with a 25-year history

Challenge: A desktop accounting system in use since 2000, including at a group of more than 20 companies. Users regularly contact support with routine questions about working with the system.
Solution: An AI support assistant that answers users based on the system’s documentation and training materials and escalates complex questions to a specialist. The assistant does not use or transmit customers’ accounting data.
Result: Accountants get answers to routine questions instantly, and the support team focuses on complex issues. AI was added to a mature product without rewriting it.

RAG
Knowledge Base
Semantic Search
Human Handoff

Internal R&D project

Knowledge base with search across documentation and scanned books

Challenge: Quickly find accurate answers across a large body of technical documentation in several versions and in scanned Ukrainian-language textbooks.
Solution: OCR of scans in Ukrainian and English, structure-aware chunking, multilingual embeddings on our own GPU server, and vector search at both chunk and document level. Every answer links to the exact page of the source, and incremental indexing reprocesses only documents that have changed.
Result: Search by the meaning of the query rather than by matching words. The solution runs entirely on our own infrastructure, with no external AI services.

RAG Pipeline
Docling
Tesseract OCR
multilingual-e5
ONNX Runtime
NVIDIA CUDA
PostgreSQL + pgvector

Pilot project

Support bot for a domain where mistakes are costly

Challenge: An emotional support bot where an inaccurate or unsafe AI response is unacceptable.
Solution: Answers based only on verified materials, retrieved through hybrid search with reranking. Moderation and risk scoring of every message, crisis routing to human help, long-term memory of previous conversations, and a set of eval scenarios to check quality before every release.
Result: An approach we apply in every field where errors are expensive: finance, healthcare and law.

Hybrid Search (RRF)
LLM Reranking
HNSW
Guardrails
Risk Scoring
Long-term Memory
Evals

Our edge: AI plus 20 years of software engineering

Most AI solutions stop at a chatbot. We connect AI to what already runs in your company.

Business systems and databasesCRM, ERP and accounting systems, including those built on Oracle, MySQL, Firebird and other databases.
Mobile, web and desktop applicationsWe add AI features without rewriting your product.
Messaging appsTelegram (including deep integration via TDLib), WhatsApp, Viber, Slack.
Connected devicesApplications that work with hardware and sensors over BLE and USB.

AI-native development

We use AI in our own work every day. Our in-house SDLC-aware Spec-Driven Development methodology builds the development process around AI agents. Every decision is recorded only after human confirmation, and requirements are traceable all the way to implementation.

Discovery: agents identify contradictions and gaps
Human Gate: confirmed by a person
Specification, UI prototype, effort estimate
Architecture and development with AI coding agents

Spec-Driven Development
AI Coding Agents
Agent Skills
Claude Code
OpenAI Codex
Traceability

How we work

Free AI assessment

We identify the processes where AI will have the greatest impact and assess how ready your data is.

1–2 meetings · free
Proof of concept on your data

We test the idea on your real documents and processes with measurable quality metrics.

2–4 weeks · fixed price
Launch and integration (MVP)

We roll the solution out to a first group of users and connect it to your systems.
Production and growth

Quality and cost monitoring, evals, new scenarios.

Why Desta

Data protection by defaultWe design solutions in line with GDPR and the EU AI Act. Deployment in your infrastructure, a private cloud or EU cloud regions.
20+ years of engineering experienceAI solutions are software first and foremost, and we know how to make software reliable.
No vendor lock-inYou can switch models without rewriting the system.
Easy collaboration with EuropeJust 1–2 hours’ time difference and direct communication with developers in English.
You own 100% of the solutionCode, prompts, agent configurations and fine-tuned models.

FAQ

Our data is confidential. Can we still use AI?

Yes. Models can be deployed on your servers or in a private cloud. We can also anonymise documents before they are processed by external AI services.

How is this different from a regular chatbot?

Our solutions answer based on your documents and data (RAG), show their sources and can take actions in your systems through agents and MCP integrations.

Can you add AI to our existing product?

Yes. We integrate AI features into existing web, mobile and desktop applications without rewriting them.

How do you control the quality of AI responses?

Through evals on real-world scenarios before every release, production monitoring, and guardrails that prevent unwanted responses and actions.

Where do we start?

With a free AI assessment. You tell us about your challenge, and we propose an approach and a prototype plan that can be delivered in 2–4 weeks.

Tell us about your challenge

We will propose a solution, estimate the timeline and prepare a prototype plan based on your data. The AI assessment is free.

info@desta.software +38 048 735 29 92