AI Development Services
Peiko provides end-to-end AI development services - from choosing the right use case to building, integrating and supporting AI features in production, for new products and existing software.
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What are AI development services?
AI development services cover the design, training, configuration, integration and deployment of AI-powered features — from generative AI and natural language processing to computer vision and intelligent automation. Depending on the task, we train custom machine learning models or configure and fine-tune existing ones, including large language models (LLMs). By combining AI with solid software engineering, Peiko helps businesses turn their data into working products: smarter workflows, automated decisions and AI features that ship to production.
BUILD CUSTOM AI PRODUCTS
Launch AI-powered products built around your data and use case. We develop custom machine learning models, generative AI features, computer vision systems, and intelligent automation tools designed for production, not just demos.
INTEGRATE AI INTO EXISTING SOFTWARE
Add AI capabilities to your current product without rebuilding it. Our team implements AI copilots, recommendation engines, NLP-powered search, and automation features while maintaining compatibility with your existing infrastructure.
AI development solutions we provide
Natural language processing (NLP)
Turn text and conversations into working business tools. Chatbots answer customer questions around the clock, intelligent document processing extracts data from contracts and invoices without manual entry, sentiment analysis shows how customers feel about your product, and smart search helps users and employees find the right information in seconds.
Computer vision & OCR
Let software see and read for your team. Computer vision detects product defects on the production line, tracks objects in real-time video, and flags issues before they reach customers, while OCR scans documents, invoices and IDs and turns them into structured data your systems can use.
AI-powered process automation
Hand routine work over to software. AI combined with robotic process automation (RPA) handles data entry, request routing, report preparation and document approvals, so your team spends less time on repetitive tasks and makes fewer manual errors. Learn more about AI for business automation.
Machine learning & deep learning models
Put your historical data to work. Machine learning models forecast demand and sales, classify documents and transactions, personalize offers for each user, and detect anomalies such as fraud or equipment failures early. Deep learning takes on more complex inputs like images, audio and large volumes of unstructured data.
Generative AI applications
Build products on top of large language models. Typical applications include AI assistants that answer questions inside your product, content generation for marketing and support, and knowledge search that finds answers across company documents and databases. Explore our generative AI solutions.
Recommendation engines
Meet the needs of your customers. Our AI-driven recommendation systems take user actions and preferences into account to provide platform-agnostic product, content, and service suggestions.
AI for blockchain & DeFi
To create blockchain ecosystems that are smarter and safer, we provide AI solutions for detecting fraud, predicting crypto markets, and optimizing smart contracts.
Decision intelligence platforms
To help businesses make informed strategic decisions based on complicated datasets, we develop platforms that combine data visualization with forecasting models and scenario simulations.
Customer experience AI
Improve support and engagement without growing the team. AI agents resolve common requests on their own, sentiment-aware routing sends frustrated customers to a human agent faster, and personalized responses and offers are based on each customer’s history. Learn more about our custom AI agents.
How we deliver AI development services
Use case & data assessment
We review your product, users and workflows to find where AI brings real value, and check whether your existing data is enough to support it. You end this stage with a validated use case and a clear view of your data readiness.
Architecture & model selection
We define data sources, APIs, security constraints and the right model type — classic ML, deep learning or LLM-based. The choice depends on your task, data and budget, so you get an architecture that fits the problem instead of the most complex option available.
Development & integration
We train or configure the models and build AI features into your product and infrastructure step by step. Each feature is tested early on your real data, so you see working results during development, not only at the end of the project.
Testing & safety controls
Before launch, we check model accuracy and edge cases, and set up guardrails, monitoring and usage limits. As a result, your AI features behave predictably with real users, handle unexpected inputs safely and keep running costs within the agreed budget.
Launch, monitoring & improvement
After launch, we track how people actually use your AI features and how good the outputs are. Based on this data, we improve models, training data and prompts, so the product keeps getting more useful instead of staying frozen at release.
AI development services across industries
Too much time spent on paperwork instead of patients? AI processes medical documents and intake forms, supports diagnostics with medical image analysis, predicts appointment no-shows and powers symptom-checker assistants. Clinics and HealthTech products reduce administrative load and give staff more time for care, while sensitive patient data stays protected.
Hard to give every learner individual attention? AI builds personalized learning paths based on each student’s progress, powers tutoring assistants that answer questions around the clock, automates grading and flags learners at risk of dropping out. EdTech platforms scale their courses without losing quality or overloading teachers.
Losing money on delays and excess stock? AI forecasts demand to keep inventory at the right level, optimizes delivery routes, predicts shipment delays and reads shipping documents with OCR. Logistics teams plan with more confidence, cut manual paperwork and react to disruptions before they hit customers.
Fraud and slow onboarding costing you customers? AI detects suspicious transactions in real time, automates KYC checks and document verification, supports credit scoring and powers assistants that handle routine client requests. FinTech products onboard users faster, reduce fraud losses and keep compliance work manageable as they grow.
Visitors browse but don’t buy? AI recommends products based on each shopper’s behavior, powers smart search that understands what customers mean, adjusts pricing to demand and answers order questions through chat assistants. Online stores raise conversion and average order value while support handles more requests with the same team.
Travelers expect instant answers and tailored offers? AI assistants help plan trips and handle booking changes around the clock, recommendation engines suggest destinations and stays based on preferences, and demand forecasting supports smarter pricing. Travel platforms convert more searches into bookings and reduce the load on support teams.
Since 2017, our software creation team has consistently delivered industry-focused development services that get results.
Why choose Peiko as your AI development company
Fast path to production
Instead of spending months perfecting a model, we release working AI functionality early and improve it based on real user feedback. You see results in your product sooner, validate the idea with actual users and invest further only where AI proves its value.
Product-first approach
We make AI decisions from the user and business perspective, not only by model metrics. Every feature is tied to a real task in your product, so you avoid investing in AI that looks impressive in a demo but changes little for your users.
Clear communication
We explain AI trade-offs in plain terms: which model fits your task, what data it needs, how much it will cost to run and what accuracy to expect. Founders and product managers make informed decisions without having to become AI experts.
Budget focused on results
We spend your budget on the AI work that supports validation and growth, not on throwaway experiments. Each stage has a clear goal and outcome, which makes it easier to plan costs and justify the AI investment to your stakeholders.
Architecture that scales
We design AI solutions with growth in mind: more users, more data and new features. The architecture handles higher load and new models without starting over, so your product stays stable as usage grows and you avoid costly rewrites later.
How Much Does AI Development Cost?
AI Consulting / Feasibility Study
$500–$2,000 Data audit, use-case identification, and a feasibility study to determine if AI is the right investment for your business.
Chatbot / Conversational AI
$4,000–$15,000 From a basic FAQ chatbot to a context-aware AI assistant with CRM integration and memory.
Computer Vision / OCR System
$10,000–$150,000 Custom vision models for defect detection, facial recognition, or document processing.
Generative AI Integration
$10,000–$100,000 Custom user experiences, content generation, and AI-powered product features.
Predictive Analytics / ML Model
$15,000–$50,000 Demand forecasting, churn prediction, fraud detection, and custom ML models trained on your data.
Enterprise AI Platform
$150,000–$500,000+ Full-scale, production-grade AI systems with custom model training and enterprise integrations.
Technologies we use
Case studies
A next-generation AI-powered trading platform that lets retail investors build, simulate, and run fully-automated ETF strategies.
We had to create a secure, real-time trading product from scratch, translate a complex vision into a clear roadmap, and keep development agile enough to absorb regular startup pivots.
Our AI development expertise
Business value of custom AI development
What Our Clients Say
We don’t just build software, we build success stories
We’ve earned a 100% Job Success score on Upwork as a result of consistent delivery, long-term client satisfaction, and predictable results.
View work historyOur work is rated 5.0 on Clutch, reflecting verified client reviews, strong professionalism, and a clear focus on scalable, business-driven digital solutions.
Read reviewsAI Development Services FAQ
No, you don’t need to prepare everything in advance. We check data readiness at the start of the project: what data you have, where it is stored, how complete it is and whether it is enough for the chosen use case. Usually, you only need to provide access to relevant data sources, such as databases, documents or CRM exports, along with a few examples of the tasks AI should handle. If the data needs cleaning or labeling, we include that in the project plan.
Custom AI development services provide scalability and a competitive edge by adapting to your unique requirements, data, and workflows. Although existing solutions can be deployed more quickly, they might not be as flexible or deeply integrated with your business operations.
We build responsible AI practices into the development process from the start. We check training data and model outputs for bias, use explainable models where decisions need to be clear to users or regulators, and follow governance frameworks that define who owns the model, how it is monitored and how issues are handled. Sensitive data is processed only within the access rules agreed with you.
We choose the stack based on your task, data and budget rather than sticking to one vendor. For generative AI, we work with large language models from OpenAI, Anthropic and Google, as well as open-source models such as Llama and Mistral when data must stay on your infrastructure. For machine learning and deep learning, we use Python with PyTorch, TensorFlow and scikit-learn, and for LLM-based features — LangChain, LlamaIndex and vector databases such as Pinecone and pgvector. Models are deployed on AWS, Google Cloud or Microsoft Azure, or on your own servers.
Yes. You can add Peiko’s AI and ML engineers to your in-house team for a specific project or on a long-term basis. They work within your processes and tools, take over tasks such as model development, data pipelines or AI integration, and share knowledge with your team along the way. If you need a full team, learn more about our dedicated development team model.
Timelines vary by complexity, but a functional MVP typically takes 8–12 weeks. More advanced solutions may range from 3 to 6 months. We provide accurate timelines after a detailed discovery and scoping phase.
The cost depends on the scope and the engagement model. In our experience, a paid AI consulting or feasibility study typically costs $500–$2,000, AI development projects range from $4,000 for a basic chatbot to $150,000 for complex computer vision systems, and enterprise AI platforms start at $150,000 and can exceed $500,000. You can also hire Peiko’s AI engineers as a dedicated team with monthly billing. The exact budget is defined after a scoping call.
You do. After the project is completed and paid for, all intellectual property rights to the source code, custom-trained models and documentation are transferred to you. Your data always remains yours: we use it only for your project and never to train models for other clients. We sign an NDA before the project starts if required. Third-party models used through APIs, such as OpenAI or Anthropic, stay under their providers’ licenses, while everything built on top of them belongs to you.

