Step 01
Discovery and product framing
We align on the business problem, data, compliance constraints, and what should be AI-native vs classic deterministic logic.
AI-native software company
An AI-native software company
Products and platforms where language models, agents, and data belong in the architecture, not bolted on at the end
We are a product engineering team for companies that want to build AI-native apps: copilots and workflows, plus systems with RAG, evaluations, and governance.
We combine mobile and backend experience with real-world LLM delivery. We run discovery, PoC, and production paths with a strong focus on cost, data safety, and keeping answer quality stable over time.
End-to-end
From UX to release
LLM + app
A product, not just chat
LLMOps
Evals and monitoring
How we work
AI-native is how you build the product
We do not just add a chat. We design loops: data, tools, models, evaluations, and policies you can operate inside your organization.
Product and UX
User scenarios, failure states, empty results, and latency - designed like any serious application.
Systems and integrations
APIs, queues, identity, permissions, and consistency with your existing stack.
Quality and regressions
Test sets and metrics so prompt or model changes do not silently break production.
Safety
Output constraints, sensitive data protections, and policies aligned with your legal context.
Cooperation process
How does our cooperation look like?
A transparent process that leads from idea to finished product
Step 02
Architecture and risk
Model choices, flows, tools, caching, and integrations. We plan guardrails, logging, and regression testing early.
Step 03
Implementation
We build backend, UI, and the AI layer: agents, RAG, copilots, model APIs, queues, and workers.
Step 04
Evaluations and quality
Test sets, metrics, prompt version comparisons, and edge cases before scaling traffic.
Step 05
Launch and operations
Cost and error monitoring, alerts, versioning, post-launch support, and roadmap iterations under real load.
Key benefits
Why choose us?
Business outcomes first—technology is the means, not the end in itself.
AI-native product
Features and flows designed around models, not retrofitted onto legacy UX.
Integrations and data
Secure connections to CRM, ERP, documents, and internal tools.
Governance
Content policies, PII handling, access control, and traceability.
Time-to-value
Fast PoCs with a clear path to production milestones.
Cost control
Model routing, caching, limits, and token usage observability.
One team goal
Product, design, and engineering share a concrete definition of AI success.
FAQ
Common questions about an AI-native software company
What is an AI-native software company?
A team that builds software where language models, agents, and data workflows are part of the product architecture from day one, rather than a one-off integration at the end.
How is this different from a basic ChatGPT integration?
A chat integration is often a single endpoint. AI-native delivery includes data flows, permissions, evaluations, cost controls, logging, and iteration tied to a real business process.
Do you only do LLM work, or also mobile and backend?
We ship full stack: mobile and web apps, backend, integrations, and the AI layer. That lets us deliver end-to-end products, not isolated prototypes.
How do you handle security and privacy?
We design data access, segmentation, model output policies, and auditability. The exact controls depend on your industry and requirements, and we define them during discovery.
How long until a meaningful first release?
It depends on scope and data readiness. We usually start with a focused PoC or MVP for selected scenarios, then harden the architecture for production scale.
Do you support after launch?
Yes: monitoring, cost optimization, quality fixes, new scenarios, and evolving agents or RAG in later iterations.
Technologies
What technologies do we use?
Modern tools and proven solutions for the best results
OpenAI
AI Platform
Claude
AI Platform
LangChain
Framework
Next.js
Frontend
React Native
Mobile
Node.js
Backend
PostgreSQL
Database
AWS
Cloud
Service scope
What does the service include?
Below is an example scope of work that we adjust to the stage and goals of the project.
Co-building an AI-native product with business stakeholders
Backend, APIs, and client apps ready for real-world load
Agents, workflows, and automation with human-in-the-loop where needed
RAG, tools, and source grounding when facts matter
Evaluations, regressions, and monitoring of answer quality
Security: policies, logs, data segmentation, access control
LLMOps: releases, prompt versions, costs, alerts
Post-launch support and roadmap evolution
Ready to start?
Schedule a free consultation and learn how we can help with your project. After our DDT process (Discovery, Design & Technology), we offer a price guarantee and a fixed-price agreement.
Preliminary estimate in 48h
Fixed price after DDT — price guarantee
No commitment
We can sign NDA
Contact
Let's talk
about the project.
Have an app idea or need technological support? Write to us — we'll prepare a preliminary analysis and estimate within 48h. Projects that go through our DDT process (Discovery, Design & Technology) come with a price guarantee and a fixed-price agreement — a key differentiator for us.
Write to us[email protected]
Visit us
GD
gmi.software Sp. z o.o.ul. Jana Heweliusza 11 / 819
80-890 Gdansk, Poland
80-890 Gdansk, Poland
NIP: 5252816287KRS: 0000830003
© 2026 gmi.software Sp. z o.o.