Valletta.Software: AI-Care

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Overview

$25,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

250 - 999

Employees

2009

Year Founded

ABOUT VALLETTA.SOFTWARE: AI-CARE

AI-Agentic development

Valletta.Software is a software engineering company located in Malta, having successfully completed over 700 projects for clients in Europe, Israel, and North America. We operate under EU regulations, accommodating US and European business hours, and communicate solely in English. We offer fixed-price contracts with no open-ended retainers or unpredictable estimates. Prior to commencing any project, we carefully define the scope, including the delivery timeline, budget, and feature set, which is then agreed upon and finalized. This approach is our standard engagement model, not an added premium option. In addition to staffing, our team augmentation service goes further. Each engineer we provide is trained in AI-assisted workflows, prompt engineering, and AI-agent orchestration. You’re not just receiving additional manpower; you are gaining a professional who works at 2-3 times the speed of a typical developer while consistently delivering documented and maintainable results. We also specialize in recovering projects that have encountered issues. This includes two main types of products: those hampered by poor engineering practices (such as flawed architecture, critical bugs, lack of documentation, and accumulated technical debt) and those created with basic coding tools that have outgrown their capabilities. We stabilize, refactor these projects, and bring them to a production-ready state, all within a fixed-price agreement. Our team possesses extensive knowledge in OpenClaw and NemoClaw. We connect large language models (LLMs) like Claude, GPT, and local models to your systems and messaging platforms, such as WhatsApp, Slack, Teams, and Telegram. We develop long-running agent runtimes, create functionalities for ClawHub, and manage secure enterprise deployments. NemoClaw enhances this ecosystem by providing additional orchestration and multi-agent coordination features. Our engineers have practical experience with Claude Code, Anthropic's agentic coding platform. They operationally utilize it in client projects rather than treating it as a mere experiment. This encompasses the integration of Claude Code into CI/CD pipelines, multi-agent development workflows, and structured code generation systems complete with review checkpoints.

Tech Stack

ASP.NET.NETAngularC#JavaScriptKotlinNodeJSPHPReact NativeSwiftTypescript

Languages Spoken

EnglishGermanUkrainian

HIGHLIGHTS

$25,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

250 - 999

Employees

2009

Year Founded

Services

Focus

Industries

Clients

Services Provided

13% Custom Web Application Development

5% Mobile App Development (iOS & Android)

7% DevOps Engineering

15% API Development & Integration

10% IT Staff Augmentation

25% AI Agent & Multi-Agent System Development

20% LLM Integration & Prompt Engineering

5% AI Strategy & Roadmap Consulting

About the Team

OUR STORY

Our Journey Since 2009, Valletta Software Development has established remote engineering teams led by experienced professionals to address critical talent shortages in various fields, including web, mobile, QA, UX, IoT, and e-commerce. Our leadership combines expertise in finance, computer science, and transformation. We have successfully completed over 1,000 projects across 11 different industries, maintain a 15% bench, employ rigorous vetting processes, conduct weekly reviews, provide detailed reporting, and enjoy a 100% success rate along with a 98% recommendation rate from our clients.

TEAM PHOTOS

Portfolio

AI GEO project for Furniture Intelligence Platform

Dreamsofa

1) Objectives: The project's aim was to develop a furniture intelligence platform that consolidates scattered market data, identifies emerging trends, facilitates topic grouping, classifies search intent, and streamlines marketing idea generation through an AI-powered RAG assistant. 2) Solutions: We created and implemented the minimum viable product (MVP) framework for the platform, which included a data intake pipeline, a setup for semantic search, integration with a vector database, query cleaning and filtering mechanisms, trend detection processes, a chat-like interface, and content generation capabilities. Additionally, we added a human review stage, documentation, and handover materials to enhance RAG features post-launch. 3) Outcomes: The platform decreased manual research efforts by 68%, tripled the speed of campaign planning, shortened content creation timelines by 57%, and elevated intent classification accuracy to 89%. The initial adoption of the MVP also boosted the speed of internal insight retrieval by 72% and established a scalable foundation for future AI-driven marketing processes.

AI-Based Agrotech Management Platform

AgroNet ZERO

Project Overview: 1) Objectives: The main aim is to integrate scattered agronomic, regulatory, and geospatial information into a single platform, automate the processes of data ingestion, normalization, and validation, facilitate agronomic impact assessments and basic recommendations, and produce a viable proof of concept that lays a solid technical groundwork for future development of a minimal viable product (MVP). 2) Approaches: We developed the technical infrastructure of the platform from the ground up, establishing a data ingestion pipeline capable of handling CSV, Excel, and GeoJSON files, creating a structured PostgreSQL database for agronomic indicators, and designing workflows for data normalization and validation. Additionally, we processed datasets from multiple states, incorporated initial calculation models, and outlined the product architecture from the early demonstration phase to the forthcoming MVP. 3) Outcomes: The solution successfully consolidated over 10 disparate data sources across more than 3 file formats, organized over 50 agronomic indicators, and decreased manual data preparation efforts by as much as 80%. Furthermore, it tripled the speed of analysis workflows, facilitated discussions with pre-seed investors, and positioned the project for the next stage of funding.

AI-Powered Book Writing & Generative Content Creat

InkSpire

1) Objectives: The client sought to revolutionize the traditional publishing industry by launching an AI-driven platform designed to speed up the book writing process. They also aimed to improve the platform's storytelling features and provide author support across various genres with minimal manual input. 2) Solutions Provided: We developed a comprehensive content engine utilizing GPT-4, prompt chaining, and sophisticated NLP techniques. Authors were able to collaboratively create stories, automatically generate chapters, and modify tone and style for different genres. 3) Outcomes: Consequently, writing time decreased by 80%, content production increased fivefold, and users successfully published bestsellers on Amazon. In the first quarter, revenue grew by 45%.

22 more projects