AI assistants & product features
Conversational assistants, summarization, and content tools integrated into the workflows your users already know.
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Service — 06
AI Integration & Cloud Solutions for Real Products
Bring practical AI into your product and run it on reliable cloud infrastructure — from knowledge assistants to deployment, monitoring, and scale.
What We Deliver
Intelligence with a solid foundation.
Knowledge search & retrieval
Search your documents and application data with retrieval-based answers, clear sources, and access-aware context.
Intelligent workflow automation
Classify requests, extract structured information, and route repetitive tasks with human review where it matters.
Cloud architecture & migration
A deployment plan built around your workload, with carefully managed migrations, storage, and service boundaries.
Deployment & scaling
Repeatable releases, background workers, caching, and scaling strategies that follow real demand.
Security, monitoring & cost control
Access controls, usage limits, observability, and evaluation checks designed into the system from the start.
Typical Stack
Tools we reach for.
- AI APIs
- Retrieval / RAG
- Vector search
- Docker
- CI/CD
- Cloud storage
- Observability
Sample stack — the final choice always follows your requirements, not our habits.
How We Work
From a useful idea to a dependable system.
01
Find the right use case
Define the outcome, review your data, and decide where AI helps — and where conventional software is the better fit.
02
Prototype & evaluate
Test a focused workflow against representative inputs, checking answer quality, privacy, latency, and cost.
03
Deploy & improve
Integrate the feature, establish monitoring and fallback paths, then refine it with real usage and feedback.
Overview
Practical AI, built on solid infrastructure.
AI is useful when it solves a specific problem: summarizing long documents, answering common customer questions, classifying incoming requests, or extracting data from files. It is less useful when added just to say a product has AI.
We start by identifying the task where AI saves real time, then integrate language models into your existing workflow with clear limits, human review where it matters, and careful handling of your data. Every feature is tested against real examples before it reaches users.
Alongside AI, we set up cloud hosting, storage, backups, and deployment pipelines so your application runs reliably and scales when traffic grows, without paying for capacity you don't use.
Example Scenario
An AI assistant for a support inbox.
Illustrative example of a typical engagement. Replace with a verified client case study.
The challenge
A support team receives a high volume of emails, many asking the same questions. Responses are slow and agents spend time searching documentation.
What we build
An AI integration that classifies incoming emails, drafts suggested replies from the company's own help content, and routes complex cases to a human agent.
The outcome
Agents review and send drafts instead of writing from scratch, routine questions are answered faster, and complex issues reach the right person sooner.
Typical Timeline
From use case to production AI.
Estimated ranges — your exact plan is set after discovery.
1 week
Use-case discovery
Identify the task, success criteria, data sources, and privacy requirements.
1–2 weeks
Prototype
A working proof of concept tested on real examples from your business.
2–6 weeks
Integration & cloud setup
Production integration, hosting, storage, monitoring, and cost controls.
1 week
Review & rollout
Quality review, staff onboarding, and gradual release.
FAQ
Questions we often hear.
Is our data used to train AI models?
We choose providers and settings that don't use your data for training, and we only send the information each feature needs.
What if the AI gives a wrong answer?
We design features with guardrails: answers grounded in your own content, confidence checks, and human review for important decisions.
How much does running AI cost?
Costs depend on usage volume. We estimate running costs during the prototype and add limits and monitoring so there are no surprises.
Which cloud providers do you work with?
We work with major cloud and hosting providers and recommend one based on your budget, location, and technical needs.
Ready to put AI to work?
Tell us what your product needs to do — we'll shape the AI and cloud solution around that goal.
