Empower
Your Startup
With Generative AI Development Services
Blend AI capabilities with your unique vision to build not just a trend-driven product, but a true market disruptor.
Generative AI Development in Numbers
AI-based projects delivered
10+
Of experience working with GenAI models and LLMs
5+ years
In-house AI products released
3
Services We Provide
Dataset Preparation and Curation
Our team collects, cleans, and structures datasets to ensure high-quality input for training. Proper curation reduces bias and gives the model a reliable foundation to learn from.
Generative AI Solutions We Built
We design and implement production-ready generative AI systems that solve real business challenges. From internal copilots to AI-powered analytics engines, our solutions are secure, scalable, and tailored to each organization's workflows and data ecosystem.
AI Assistants & Copilots
Custom AI assistants embedded into internal tools, SaaS platforms, or customer-facing products. These systems automate communication, task execution, and knowledge retrieval across departments.
ChatGPT Enterprise
Microsoft Copilot
AI-Powered Knowledge Systems
Secure AI knowledge bases trained on internal documentation, policies, and structured databases. These systems use retrieval-augmented generation (RAG) to provide accurate, context-aware answers.
Notion AI
Confluence AI
AI Content Generation Platforms
AI engines designed to generate marketing copy, product descriptions, reports, emails, and internal documentation at scale. These platforms maintain tone consistency and brand alignment.
GrammarlyGO
Jasper
AI Document Processing & Automation
Intelligent document systems that extract, classify, and structure data from contracts, invoices, financial statements, and compliance reports. These solutions combine OCR, NLP, and generative AI to automate document-heavy workflows and reduce processing time.
Rossum
Hyperscience
AI-Powered Analytics & Insights
Generative AI systems integrated with data warehouses and BI tools to produce real-time summaries, forecasts, and executive-ready insights. We build AI layers that sit on top of analytics platforms, turning raw dashboards into natural-language business intelligence.
Power BI Copilot
Metabase AI
Project Timeline
*The provided timelines reflect a medium-sized project with standard functional and technical complexity.
Discovery
1–2 weeks
Discovery
We explore the business context, product goals, and user needs. This stage helps define the problem space, constraints, and success criteria before any solution is designed.
People
Product Owner
Business analyst
Project ManagerTools
Notion
Google Meet
MiroRequirements Definition
1–2 weeks
UX/UI Design
2–4 weeks
Development
3–5 weeks
Testing
1–2 weeks
Release
2–5 days
Case Studies
Real AI products we shipped — from LLM-powered content detection and interview analysis to generative outreach automation and real-time voice moderation.
Automated Meeting Insights
Used Whisper + GPT-4 with chained prompts for structured extraction, added vector search for interview retrieval, and cut inference costs 60% via streaming and caching.
Companies That Build With Us
Success Stories We've Written Together
EkosLive — cloud astrophotography platform
Seraf — investment portfolio management
ExistLive — event management platform
SHEQSY — lone worker safety platform
FAQ
We can build assistants, internal knowledge tools, automation workflows, content generation systems, and products that use LLMs as part of the user experience.
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