CodeBase Coders delivers end-to-end AI services and solutions for startups, SMBs and enterprises: AI consulting, custom AI and generative AI development, AI agents, chatbots and AI integration into the software you already run. We build AI that works reliably with your real data, security rules and workflows, and we stay to maintain it.
Many AI projects stall after an impressive demo because the model never meets real data, real users or real security requirements. Our AI services and solutions start from your workflows, systems and constraints, so what we build keeps working after launch and keeps improving as your data and usage grow.
AI is only worth building when it moves a business number. These are the outcomes we design every engagement around.
Automate repetitive tasks such as data entry, document review, ticket triage and reporting, so teams spend time on judgement instead of copy-paste.
Give customers instant, accurate answers around the clock through AI chatbots and assistants that hand over to a person when needed.
Turn scattered data into forecasts, risk scores and plain-language insights that managers can act on.
Recommend the right product, content or next step for each user based on behaviour, not fixed rules.
Detect fraud and anomalies earlier, and keep AI outputs inside clear guardrails for privacy, accuracy and compliance.
Start with one high-value use case, prove it, then extend the same foundation across teams without rebuilding.
Whether you need a clear AI strategy, a single AI feature inside an existing product or a complete AI platform, our artificial intelligence services cover each stage, from consulting and proof of concept to development, integration and ongoing support.
AI readiness assessment and roadmap
Use-case discovery and prioritisation
Build vs. buy and model selection
AI governance and responsible AI policies
AI consulting helps you decide where AI will pay off before you invest in building it. We review your processes, data and systems, rank use cases by value and feasibility, and deliver a practical roadmap with architecture, budget ranges and success metrics, including an honest answer when AI is not the right tool.
Proof of concept and AI MVP
Custom AI applications and SaaS features
Model training and fine-tuning
Evaluation and accuracy testing
Our custom AI development services turn a validated idea into working software. We design the data pipeline, choose or train the model, build the application around it and test it against real-world cases, so the result fits your workflow instead of forcing your team to fit a generic tool.
RAG knowledge assistants
Content and document generation
LLM fine-tuning and prompt engineering
Copilots inside your product
Our generative AI development services build applications on large language models (LLMs) and multimodal models: assistants that draft, summarise and answer from your knowledge base, content and code tools, and document intelligence. We use RAG, prompt engineering and fine-tuning where each one fits, with guardrails against hallucinations and data leaks.
Task-automation AI agents
Multi-agent workflows
Tool calling and API actions
Human-in-the-loop approvals
AI agents go beyond chat. Agentic AI systems plan a task, call your APIs and tools, check their own work and complete multi-step processes such as qualifying leads, reconciling records or preparing reports, with approval steps and logs so a person stays in control.
Customer support chatbots
WhatsApp AI assistants
Voice bots and voice agents
Internal HR and IT helpdesk bots
We build AI chatbots and conversational AI for websites, apps, WhatsApp and internal tools. They understand natural language, answer from your own content, capture leads, book appointments and hand complex conversations to your team with the full context.
OpenAI, Claude and Gemini API integration
AI inside CRM and ERP workflows
Workflow and process automation
Legacy system AI enablement
Our AI integration services add AI to the systems you already rely on, including CRMs, ERPs, helpdesks, e-commerce platforms and custom software, through secure APIs and middleware. Your team gets AI inside familiar tools rather than another disconnected app.
Predictive analytics and forecasting
Recommendation engines
Fraud and anomaly detection
Churn and risk scoring
For prediction and pattern-recognition problems, our machine learning development services build models trained on your historical data: demand and sales forecasting, churn and risk scoring, recommendations and anomaly detection, deployed with monitoring so accuracy does not quietly drift.
OCR and document data extraction
Visual quality inspection
Object detection and counting
Video analytics
Our computer vision development turns images and video into structured data: reading documents and IDs, spotting defects on a production line, counting stock, or monitoring sites for safety events, running in the cloud or on edge devices.
Contract and invoice processing
Text classification and routing
Sentiment and feedback analysis
Multilingual search and translation
Natural language processing (NLP) solutions that read, classify and extract information from emails, contracts, invoices, forms and support tickets, then route it into the right system, cutting hours of manual reading from back-office work.
Model monitoring and evaluation
Retraining pipelines
LLM cost and token optimisation
AI maintenance and support
AI systems need care after launch. Our MLOps and LLMOps services monitor accuracy, latency and cost, run evaluations when models or prompts change, retrain on new data and keep security patches and model versions up to date.
Tell us the problem you want AI to solve. We will tell you whether AI is the right fit, which approach suits your data and budget, and what a first version would involve.
Our AI solutions for business are shaped around specific jobs to be done in sales, service, operations and finance, each connected to the data and tools that team already uses.
Assistants that answer customer and employee questions from your own knowledge base, complete simple requests and escalate to a person with the conversation history attached.
Recommendation systems that learn from browsing, purchase and engagement signals to suggest relevant products, content and offers, and adjust as behaviour changes.
Models that score transactions, sign-ups and claims in real time, flag unusual patterns for review and explain why each case was flagged.
AI that classifies incoming tickets and emails, drafts replies for agents, summarises long threads and routes each case to the right team.
Extract data from invoices, purchase orders, contracts and forms, validate it against business rules and push it into your ERP or accounting system.
Forecast demand, sales, cash flow or maintenance needs from historical and live data, with dashboards that show the drivers behind each prediction.
Score and enrich leads inside your CRM, draft personalised follow-ups and surface the accounts most likely to convert so sales teams prioritise well.
Search that understands questions, not just keywords, across documents, wikis and tickets, returning answers with links to the source and respecting user permissions.
We are a software development company first, which is why our AI work holds up in production. Every AI feature we ship comes with the engineering around it: clean integrations, access control, testing, monitoring and documentation, so your team can trust it and run it.
We bring AI to industries where data is plentiful but manual work still slows teams down. Explore how AI fits into the platforms we build for each sector.
The same AI building blocks solve very different problems in each sector. A few examples of where they deliver value:
Summarise clinical notes, automate appointment and intake workflows, and support triage, with patient data handled under the privacy rules that apply.
Real-time fraud scoring, automated KYC document checks, credit risk models and AI assistants for customer queries.
Product recommendations, smart search, AI-written product descriptions and demand forecasting that reduces overstock and stockouts.
Route and load optimisation, delivery-time prediction and automated processing of shipping documents.
Predictive maintenance from sensor data and computer-vision quality inspection on the production line.
Personalised learning paths, AI tutors that answer from course material and automated grading support for teachers.
Property valuation models, lead qualification chatbots and automatic extraction of data from listings and contracts.
Store and online demand forecasting, dynamic pricing support and customer-behaviour analytics across channels.
We choose tools for each project based on accuracy, cost, data-privacy requirements and what your team can maintain, combining proven machine learning frameworks, leading LLMs and cloud AI platforms.
Python
PyTorch
TensorFlow
Scikit-learn
Hugging Face
OpenAI GPT
Anthropic Claude
Google Gemini
LangChain
pgvector / Pinecone
OpenCV
Pandas
Apache Spark
Databricks
MLflow
AWS Bedrock & SageMaker
Azure OpenAI & Azure ML
Google Vertex AI
Docker
Kubernetes
FastAPI / REST APIs
A structured process keeps AI projects predictable. Each phase ends with something you can review, whether a roadmap, a working prototype, test results or a live release, so you can decide how to continue based on evidence.
We map the business process, agree on the problem AI should solve and define how success will be measured.
We review what data you have, its quality and access rules, and plan any cleaning, labelling or integration work needed.
We choose the models and architecture, then build a focused proof of concept to test feasibility on your real data.
We build the full solution, including the application, integrations and guardrails, and test accuracy, safety and performance against agreed benchmarks.
We release to your cloud or on-premise environment, connect it to your existing systems and train your team to use it.
We monitor quality, usage and cost, retrain or update models as data changes and add capabilities as adoption grows.
Share what you want to achieve with AI. We will come back with questions, a suggested approach and next steps.
Discuss your idea, data and goals with our AI engineers.
Receive a recommended approach with scope, timeline and cost estimate.
Agree the plan and start with discovery or a proof of concept.
AI services and solutions cover everything needed to put artificial intelligence to work in a business: consulting to find the right use cases, development of custom AI models and applications, integration of AI into existing software, and the ongoing monitoring and maintenance that keeps AI accurate. Typical solutions include chatbots, AI agents, document processing, recommendation engines, predictive analytics and computer vision.
The cost of AI development depends mostly on scope and data. The main factors are:
A focused proof of concept costs far less than a full production platform, which is why we usually recommend starting there. After a short discovery call we provide a written estimate for your specific project.
As a rough guide, a proof of concept often takes a few weeks, a production-ready first version a few months, and larger platforms with many integrations longer. The timeline depends on data readiness, the number of integrations, approval processes and how much custom model training is needed. We confirm a timeline after discovery.
Most businesses do not need to replace their systems to use AI. We connect AI to your CRM, ERP, helpdesk, website or custom software through secure APIs and middleware, so AI features appear inside the tools your team already uses. Learn more about our AI integration services.
Traditional machine learning predicts or classifies, for example scoring a transaction for fraud or forecasting demand. Generative AI creates new content such as text, summaries, answers, images or code, usually with large language models. Many real solutions combine both: an ML model decides, and a generative model explains or drafts the next step.
AI as a Service means using AI capabilities, such as language models, speech, vision or ML platforms, through cloud APIs instead of building everything from scratch. It lowers upfront cost and speeds up delivery. We often build on AIaaS platforms like OpenAI, Anthropic, Google Vertex AI, AWS Bedrock and Azure OpenAI, and add the custom logic, data connections and guardrails your use case needs.
It can be, when the system is designed for it. We limit which data the AI can access, use providers and settings that do not train on your data, offer private or regional deployments where required, and add access control, logging and defences against prompt injection. We also align the design with the data-protection regulations that apply to your business, and our AI governance consulting services can set the wider policies and controls.
Not always. Generative AI solutions such as chatbots and knowledge assistants can work with your existing documents from day one. Custom predictive models do need enough historical data of reasonable quality. Our data analytics and AI readiness assessment tells you which approach your current data supports.
CodeBase Coders helps you go from idea to working AI: we identify high-value use cases, build proofs of concept, develop custom AI, generative AI, AI agents and chatbots, integrate them with your existing systems and support them after launch. For strategy and readiness, see our AI consulting services; for chatbots, our AI chatbot development services; for autonomous agents, our AI agent development; for the engineering side, our AI development services. Contact us to discuss your AI project, or explore more on the CodeBaseAI page.
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