Hire AI Developers That Deliver Real-World Automation
Looking to hire AI developers for production?
We are a custom software development company of 100+ engineers focusing on AI development, data engineering, workflow automation, LLM integrations, and multi-agent systems.
We Solve For: If your processes are manual, your team is overwhelmed, and AI projects continue to stall, we'll take care of that. We offer AI developers for hire and cross-functional squads to design, build, and ship production-ready AI features with measurable business impact.
PARTNER
PARTNER
FEATURED IN
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100+
software engineers
18+
years in Data Engineering
92%
Client Retention Rate
37+
AI solutions delivered
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01
AI-Powered Web & Mobile Platforms
AI tailor-made to fit your core infrastructure. We develop personalized ERP and CRM, fleet management solutions, loyalty apps, and enterprise portals that natively include AI automation and prediction algorithms and intelligent agents.
02
LLM Integration & Fine-Tuning
Hire generative AI developers who will apply GPT-4, Claude, Llama, or Gemini in your product. We offer leading-edge instant-on engineering, RAG pipelines, vector search, domain fine-tuning, and production-grade AI system deployment.
03
AI Microservices
Make lean, modular artificial intelligence components that snap into your infrastructure without disrupting it. We are experts in integrating AI software for recommendations, forecasting, NLP processing, computer vision, scoring engines, and anomaly detection.
04
Data Engineering for AI
According to the company, "Powerful AI model development is built on strong data foundations. We construct pipelines, ETL/ELT flows, data lakes/warehouses, and feature stores, along with database optimization – so clean, organized data is prepared for ML and analytics.
05
AI Agents & Workflow Automation
Want to hire Gen AI developers for AI and Robotics? We develop multi-step agents for CRM/ERP workflows that process email, lead qualification, customer support, scheduling, and operations task execution with platforms like LangGraph or even CrewAI.
06
Predictive Analytics & Forecasting
Use of AI engineers to turn historical data into insights for the future. We build demand forecast, churn prediction, risk scoring, and lead scoring, KPIs prediction models — which help C-levels take data-driven decisions before it happens.
05
RAG Knowledge Assistants & Chatbots
Build generative AI applications that become the corporate knowledge base. We create internal AI assistants to search your documents, SOPs, PDFs, and databases by using embeddings and vector search — bringing to the fingertips (or clients), your company's institutional knowledge in the form of a chat interface.
01
AI Talent Hiring Is a Months-long Affair — Results Are Not Optional Right Now
It takes 3–6 months to find AI engineers, and this is stopping products from reaching the market. You need to hire remote AI developers who ship features in weeks, not quarters.
02
Your Team Doesn't Have AI/ML Skills to Construct "AI-Driven" Features
You don't have dedicated AI talent in-house to develop LLMs, prediction models, or automation — so your roadmap is slowing down.
03
AI Experiments Aren't Making It out of the Lab and Into the Business
You have prototypes, demos, or internal tests, but nobody to produce the APIs, pipelines, monitoring, and scalable deployments required for production.
04
AI Isn't Ready for Data Yet — Pipelines, Quality, and Structure are Lacking
AI features will not function properly if data is fragmented, incomplete, or inconsistent.
05
In-House Developers Are Swamped and Can't Add AI to Their Plates
Your backend/frontend team is concentrated on essential product things and doesn't have surplus time to experiment with AI, automation, or LLM integrations.
06
Lack of an AI Roadmap and LLM Adoption Starting Point
Leadership says it wants AI, but it is not clear what use cases make sense, what to build first, or how to measure ROI.
07
Your Platform Needs AI Capabilities, but You Don't Want to Completely Rebuild.
AI may need microservices, APIs, and data flows to be integrated — but refactoring the entire system simply is not an option.
06
Current Automation or AI Features Break and Don't Scale
Scripts, bots, and prior forays into AI fail under load, crash when the UI changes, or need to be manually fixed all the time.
How an LLM-Powered System Streamlined Contract Analysis by 70%
A US-based company founded by former Amazon and Microsoft engineers was developing a SaaS platform for construction and legal teams to streamline contract analysis. They needed to speed up and scale document processing. With the LLM-powered solution we developed, they automated analysis workflows, achieving 70% faster processing and 90% higher accuracy across all document types.
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How an LLM-Powered System Streamlined Contract Analysis by 70%
AI Platform Revolutionizing Healthcare Insights
A UK healthcare market intelligence company partnered with Dataforest to drive digital transformation. We developed an AI-powered enterprise management platform that automated core processes such as data collection and report generation with deep analytical insights. With dynamic web scraping, AI-based deduplication, and GenAI data enrichment, the solution cut 9,600+ manual hours monthly and doubled productivity—delivering significant operational gains.
AI Platform Revolutionizing Healthcare Insights
Real-Time AI Voice Agent for Cold Calling
We developed a real-time voice-to-voice AI agent for the client, one of the top affiliate CPA networks. It delivers human-like conversations, handles noisy environments, and integrates with the client’s CRM and ATS. Trained on sales data, it boosts performance with <450 ms response time and a 1:1–1.5 sales quality ratio vs. human agents.
AI-Powered Cold Calling: Real-Time Voice-to-Voice Conversations
Reporting & Analysis Automation with AI Chatbots
The client, a water operation system, aimed to automate analysis and reporting for its application users. We developed a cutting-edge AI tool that spots upward and downward trends in water sample results. It’s smart enough to identify worrisome trends and notify users with actionable insights. Plus, it can even auto-generate inspection tasks! This tool seamlessly integrates into the client’s water compliance app, allowing users to easily inquire about water metrics and trends, eliminating the need for manual analysis.
Automating Reporting and Analysis with Intelligent AI Chatbots
All Success Stories
01
↓ 60–80% of manual man-hours in core operations
Our multi-agent workflows and AI automation remove the boring parts of support, lead qualification, scheduling, internal processes, etc., leaving teams to do the more high-value tasks.
02
50–70% Quicker time to market for new product features
LLM integrations (GPT-4, Claude, Llama) ship in weeks to provide AI search, chat, document understanding, and domain co-pilots in your platform.
03
40%–60% increase in operational efficiency with AI agents
Agentive systems orchestrate the tasks across CRMs, ERPs, ticketing systems, and internal tools — automatically routing emails, running through tasks and follow-ups without human intervention.
04
3× faster processing of documents and media using Computer Vision
CV pipelines automate data extraction from text, forms, IDs, invoices, labels, product images, and inspections—reducing manual data entry and verification efforts.
05
30–50% reduction in support volume with AI virtual assistants
LLM-powered chatbots can take care of FAQs, onboarding questions, account queries, troubleshooting, and even internal helpdesk scenarios — automatically solving routine requests and allowing human agents to focus on those with greater complexity.
Technologies Are Available If You Hire an AI Agent Developer
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Claude
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Llama
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LangGraph
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CrewAI
Gemini
ChatGPT
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Steps to Hire Expert AI Engineers
We follow a rigorous, transparent process to refine your requirements and deliver the AI consulting services and specialized engineering talent your team needs.
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Requirements & Stack Review
We analyze your technical needs to ensure the right fit.
01
Engineer Selection & Profiles
We present top-tier talent from our AI development company, tailored to your domain.
02
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Technical Interview with Your Team
You verify the skills and cultural fit of the engineers.
03
Onboarding & Access Setup
Seamless integration into your environment and CI/CD pipelines.
04
Weekly Delivery & Reporting Cadence
Transparent progress tracking and consistent code delivery.
05
Articles
All publications
April 28, 2025
19 min
Your Guide into Top AI Tools for Business & Comparison Table
May 9, 2025
7 min
AI Development Services Company: Domain Expertise + AI/Machine Learning
September 2, 2025
12 min
Generative AI Strategy: Fix Problems You Can Measure
FAQ
How long does it take to recruit an AI developer who understands LLMs and AI agents?
We can usually supply engineer profiles in 2–5 days. And when you're ready to get started, the entire onboarding process is measured in days, allowing us to accelerate your AI development team velocity almost overnight.
What are the skills to look for in an AI developer focused on custom AI and data engineering projects?
Seek a mix of data engineering (Python, SQL, ETL) and ML skills (TensorFlow, PyTorch, LangChain). Also, first-rate developers will need to have familiarity with backend integration if AI system development is not to be theoretical but scalable.
How do engineers work with third-party AI tools compared to custom workflows?
What we're looking for: Our engineers are experts at API and microservice-based AI software integration. We facilitate data flow between third-party models (such as OpenAI or Anthropic) and your in-house systems (CRM, ERP), for seamless automated ecosystems.
What are the best practices to manage communication and projects with remote AI developers?
Our engineers will work directly in your current communication tools (Slack, Teams, Jira). In case you decide on a squad model, we assign a Project Manager to arrange sprint planning and reporting, so our remote software development team meets your needs head-on.
How can I assess the reliability and quality of an AI developer's past work?
We include real-world case studies and technical interviews. Our AI consulting services roots mean our engineers are screened not only for coding capabilities, but also for their ability to produce production code in highly complex enterprise environments.
What are the legal/privacy concerns that one should address when hiring AI developers?
We sign very detailed NDAs and have strict data security procedures in place (including GDPR and SOC2 compliance where applicable). We guarantee that the client 100% owns the IP of all code and models constructed.
Will I be able to obtain support and maintenance in the long term after initial development has been done?
Yes. Whether you are looking to hire dedicated AI devs or go for a fixed-scope model, we provide post-deployment support packages which include model monitoring and retraining - along with regular maintenance of your environment.
What are the warning signs to look out for when selecting an AI development partner online?
Stay away from partners who promise "magic" and don't tell you what data they need. Trained on good data. It's always a good sign when the company developing your AI implementation is focusing on how to make your brand more ready for AI, as opposed to who wrote their marketing copy.
What if these AI models underperform in production, or their predictions stop being accurate after some time?
We develop MLOps pipelines to track model drift and performance decay. Our engineers establish that automated retraining triggers and alert systems are in place so your custom AI solutions stay accurate as time goes on.
How do you manage IP ownership and confidentiality when dealing with confidential business data?
DATAFOREST guarantees 100% Client IP ownership. We do not use your proprietary data to train our own models or sell it to third parties.
Can your AI developer help us determine whether we really need AI or if a simpler solution would suffice?
Absolutely. We are focused on the right solution rather than the AI solution as a strategic partner. We frequently advise conventional engineering approaches if they provide a better ROI and stability compared to a convoluted path of AI model development.
How fast can you go from a single AI developer to an entire AI team if our project becomes larger?
We keep a bench of vetted engineers. In 2-4 weeks, we can grow your team from one developer to an entire cross-functional team as your project needs expand!
Let’s discuss your project
Share project details, like scope or challenges. We'll review and follow up with next steps.
