Generative AI Solutions
Generative AI Solutions
We help companies integrate generative AI into products and business workflows – from automating complex tasks to building intelligent generative AI services. Our solutions work with real data, context, and practical use cases.
Who are generative AI services for?
Generative AI services deliver the most value when they work with real business processes, data, and company knowledge. Our approach is targeted at organizations with complex operational structures that want to use AI to improve business efficiency and scale.
We work best with teams that:
Work at scale
Companies with 100+ employees or businesses with a high volume of transactions, customer inquiries, or operational processes where automation can make a tangible impact.
Have dispersed corporate knowledge
Information is stored in different systems, documents, CRMs, internal tools, and databases, and is difficult to quickly find or use.
Require controlled and transparent AI
A solution that works with corporate data, adheres to internal policies, provides traceability of responses, and meets security requirements.
Want practical results
Teams that expect to get a measurable business impact from AI solutions within 8-12 weeks by integrating them into real-world workflows.
What’s Slowing You Down the Most?
In many companies, the most valuable resource – team time – is wasted on information retrieval, manual document processing, and endless repetitive tasks. Choose the problem that slows down your processes the most – this is where generative AI development services can have the greatest impact.
Support & service overload
Support teams spend time searching for information, repeating responses, and escalating issues rather than quickly resolving customer requests.
Knowledge chaos (docs, policies, SOPs)
Corporate knowledge is scattered across documents, tools, and databases; information is difficult to find, verify, or trust.
Document-heavy workflows
Processes that work with a large number of documents: data extraction, classification, policy checks, and approvals.
Sales enablement & proposals
Preparing RFPs, proposals, resumes, and follow-up materials takes days or even weeks of a team’s time.
Ops exceptions & triage
Tickets are misrouted, non-standard cases pile up, and SLAs begin to break.
Engineering throughput
Specification preparation, QA processes, and internal tools create bottlenecks that slow down development.
Business Outcomes You Can Measure
Custom generative AI development services only make sense when they deliver measurable results. That’s why we define clear success metrics with our team before the launch, and track them during the pilot to understand the real impact on the business. Below are the outcomes we target.
Time-to-answer
Faster access to answers for customers and employees – less time spent searching for information and processing requests.
Consistency
Standardized answers, documents, and solutions that comply with company policies and regulations.
Cycle time
Speed up processes related to documents, reviews, approvals, and internal workflows.
Decision speed
Faster decision-making thanks to access to structured and verified corporate knowledge.
Cost-to-serve
Reduce processing requests and operational costs through automation and reduced manual work.
Operational visibility
Better process transparency: traceability of answers, AI use, feedback, and system analytics.
Understanding the Problem before Designing the System
Most AI initiatives fail because they start with tools instead of problems. We begin by understanding where work slows down, where errors repeat, and where decisions stall – then design the simplest path with generative AI product development to measurable impact.
Problem clarity
First, we analyze the problem: where exactly the pain occurs, what constraints affect the process, who is involved in decision-making, and what systems or data are already in place within the company.
Success criteria
Next, we determine what success will look like: which KPIs need improvement, what results will be considered sufficient for the pilot, and what threshold values indicate that the solution is working.
Shortest path
After that, we develop a pilot scenario to quickly test the solution’s value in a real process, deliver a measurable result, and lay the foundation for safe scaling.
Generative AI Solutions Built into Real Workflows
Generative AI is most useful when it becomes part of everyday workflows. We build generative AI solutions that integrate with existing systems, leverage enterprise data, and help teams make faster decisions, automate routine tasks, and improve work quality. Below are examples of solutions we help implement – from customer support to engineering processes.
Generative AI Solutions Development: Support Copilot
Knowledge Assistant (RAG) with Permissions
Generative AI Services: Document Intelligence
Proposal & RFP Automation
Generative AI Solutions for Ops Triage & Routing
Faster Engineering with GenAI Development Services
Connecting Generative AI to Your Knowledge Sources
Generative AI only delivers true value when it works with real company data. We help connect AI to your systems, documents, and knowledge sources so that it works within the existing processes, access policies, and tools that teams already use every day.
Connect to Knowledge Sources
AI connects to various sources of knowledge within the company – from documents and internal knowledge bases to CRM systems, support systems, wikis, and file repositories. This allows the system to work with real business context, rather than abstract data. As a result, the answer, prompts, or generated materials are based on information that is already used in the team’s work.
Respect Roles and Permissions
All integrations take into account the user roles and access rights already configured in your systems. AI sees and uses only the information that a specific employee has access to. This approach allows you to maintain control over data and ensures compliance with internal security policies due to the best generative AI solutions for enterprises.
Build a Clean Retrieval Layer
To ensure AI answers accurately and is grounded in verified data, we create a specialized retrieval layer to access corporate knowledge. It structures information, finds relevant sources, and transfers their models to generate an answer. This avoids inaccuracies and provides transparency: the user can always see which sources the answer is based on.
Integrate into the Tools People Already Use
Instead of creating a separate “AI portal,” we integrate custom generative AI solutions into the tools teams already use. These could be support systems, CRMs, internal workflows, or corporate chat rooms. As a result, AI becomes part of the usual processes and helps teams work faster without changing how they work.
Generative AI Development Services: Model & Architecture Strategy
Strong custom generative AI solutions start with the right system architecture. We define the model, data approach, and control mechanisms to ensure AI operates consistently and predictably, delivering real business value.
LLM selection
We select a model based on the task, security requirements, and budget. It can be OpenAI, Anthropic, or open-source solutions.
RAG vs. fine-tuning vs. hybrid
We determine which approach is best suited for your scenario – retrieval (RAG), fine-tuning, or a combination of both.
Guardrails & prompt architecture
We design a system of prompts and constraints to ensure that AI works predictably and complies with company policies.
Evaluation framework
We create a quality assessment system that evaluates the accuracy of answers, completeness of information, and control of hallucinations.
Cost control & token optimization
As a generative AI development service provider, we optimize model and token usage to ensure the AI system scales without uncontrolled cost growth.
Generative AI Solutions Development: the Shortest Path to Impact
01. AI Use-Case Diagnostic (1-2 Weeks)
In the first stage, we identify the most promising AI scenarios for your business. A short list of use cases is formed, technical feasibility is assessed, and success metrics and possible risks are determined. The team receives a clear plan for the pilot project.
02. Prototype + Evaluation Setup (2-4 Weeks)
Next, a working prototype of the solution is created along with a quality assessment system. We create test datasets, define basic metrics, configure guardrails, and test the system’s performance in real-world scenarios.
03. Pilot in a Real Workflow (4-8 Weeks)
After that, generative AI technology services are integrated into a real workflow. We connect the necessary systems, configure monitoring, collect user feedback, and verify that the defined success metrics are met.
04. Production & Scale (Ongoing)
When the pilot proves its effectiveness, the solution goes into production. We help scale the system, train teams, implement governance, and continuously improve AI solutions based on new data and feedback.
Custom Generative AI Solutions: AI Governance & Ownership
Generative AI as a service only works when it has clear accountability and clear rules for use. We help companies create an operating model where AI is controlled, gradually improved, and actually used by teams. This includes rules for use, control processes, escalation mechanisms, and feedback systems.
AI usage policies
Human-in-the-loop design
Escalation rules
Feedback loops
Internal AI champions training
Safety First: Built for Enterprise Trust
For many organizations, the first question before adopting AI is simple: what happens to our data? We provide generative AI solutions development with security, access control, and regulatory constraints in mind, ensuring that AI operates within company policies and does not introduce additional risk to the business.
Data minimization and access control
We use the principle of least privilege: AI has access only to the data necessary for a specific scenario. This helps minimize risks and maintain control over sensitive information.
Audit logs and traceability
All interactions with AI can be tracked. The system stores logs of requests, responses, and the sources used, allowing you to review AI output and provide transparency for internal audits.
Policy-aware retrieval
AI works only with approved sources of information. The retrieval layer considers access policies and uses only data that complies with corporate rules and requirements.
Deployment options aligned to constraints
We select the deployment format based on the companyʼs requirements: cloud, hybrid, or private. This allows you to implement AI even in environments with strict security and infrastructure restrictions.
NDA-ready delivery process
We work with corporate clients in a confidential manner and sign NDAs at the early stages of the project. The interaction process is designed to ensure data protection before technical work begins.
Data sovereignty, compliance mindset & hallucination control
The AI system is designed with data storage requirements, corporate security standards, and response quality control in mind. This includes practices that help reduce the risk of hallucinations and ensure the reliability of results.
Explore What We've Built
What You Get in the First 10 Business Days
Within the first 10 working days, the team gets a clear understanding of where generative AI solutions development can have the greatest impact and how to safely test it in practice. The result is a concrete pilot plan with defined success metrics and a clear implementation path.
Prioritized AI Use-Case Map
We create a shortlist of potential AI scenarios and rank them based on two key criteria: expected business impact and implementation complexity. This allows us to identify where AI can deliver the most value, and do so most quickly.
Technical & Data Feasibility Review
We analyze available data, existing systems, and technical or organizational constraints. This helps us understand how realistic it is to implement the selected scenario and what integration of generative AI technologies may be required.
Success Metrics & Acceptance Criteria
We define what success will look like. Key performance metrics and thresholds are set to show that the generative AI pilot is working and can scale.
Risk & Governance Outline
A basic risk management plan is formed: how will the reliability of AI be monitored, what security mechanisms will be used, and how will responsibility for the system be organized.
Pilot Scope & Implementation Roadmap
We define a clear scope of the pilot project and create a roadmap that shows the shortest path from idea to a working AI solution in a real process.
Most of our clients are based in the US because of the tight business connections between the US and Eastern Europe. Additionally, the Middle East, especially Saudi Arabia and the UAE, is becoming another key region for us.
Our services
Related services
RAG Development Services
Developing RAG systems that connect generative AI to corporate data, documents, and knowledge bases, providing accurate and verified answers.
AI & ML Services
Design and development of AI/ML solutions for process automation, data analysis, and creation of intelligent products integrated into business systems.
AI Prototyping
Rapidly creating AI prototypes to validate ideas, test use cases, and assess the potential value of a solution before full development.
Our partners
Quality of Our Custom Software Company Is Proven
Our partners include companies from the Inc. 5000 and Europe's 1000 Fastest-Growing Companies
Our partners include companies from the Inc. 5000 and Europe's 1000 Fastest-Growing Companies
Good To Know
Do we need to hire specialized AI engineers to maintain the system?
What is the pricing model for GenAI services?
Can generative AI automate document workflows?
Which industries and teams benefit most from generative AI?
What are the main risks of generative AI adoption?
What’s the best first step to adopt generative AI in our organization?
Ready to bring your idea into reality?
- 1. We'll sign an NDA if required, carefully analyze your request and prepare a preliminary estimate.
- 2. We'll meet virtually or in Dubai to discuss your needs, answer questions, and align on next steps.
- Careers → careers@lumitech.coPartnerships → partners@lumitech.co
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Prefer a direct line to our CEO?