AI Development Services That Ship Production Systems, Not Prototypes
AI development services cover the design, build, integration, and maintenance of AI systems such as LLM applications, AI agents, machine learning models, and computer vision pipelines. Pixel Web Solutions is an AI development company that takes these systems from data readiness to live deployment, then keeps them accurate in production.
Get your free AI development roadmap
Tell us the outcome you want. A senior AI engineer will map the fastest path to a working system, in 30 minutes, at no cost.
- A scoped build plan for your highest value use case
- An honest read on feasibility, data gaps, cost, and timeline
- Clear next steps, whether or not you work with us
70
AI and software projects delivered
6
Industries served
12
Years building production software
6
End users touched by systems we built
Most AI builds die between the demo and production. Ours don't.
The gap is rarely the model. AI projects stall because the data is not ready, the system has no evaluation harness, and no one owns it after launch. Our AI development services close all three gaps in the same engagement, so the system reaches real users and stays accurate once it gets there.
The demo trap
A prototype that impresses in a meeting will not survive real inputs. We build with production data, edge cases, and failure modes from day one, so the first demo and the launch version are the same system.
The data gap
Most AI failures are data failures. Before any model work, we audit what data exists, what is usable, and what has to be created, then design the pipeline that keeps it flowing.
The ownership gap
Model accuracy decays. Without monitoring, evaluation, and retraining, an AI feature quietly gets worse. Every build ships with logging, evaluation sets, and a retraining plan you control.
Our AI Development Services
Pixel Web Solutions delivers nine core AI development services, from generative AI applications to computer vision and MLOps. Each one can be delivered as a standalone build or as part of a full AI product engagement.
Custom AI Software Development
End-to-end AI products built around your workflow, not a template. We handle architecture, model selection, backend, frontend, and deployment as one team.
Generative AI and LLM Application Development
Applications built on GPT, Claude, Gemini, Llama, and Mistral, using retrieval augmented generation (RAG), prompt orchestration, and fine-tuning where it earns its cost. Includes hallucination control and citation grounding.
AI Agent Development
Autonomous and semi-autonomous agents that take actions inside your systems: tool calling, multi-step reasoning, human-in-the-loop approvals, and full audit trails.
Machine Learning Model Development
Custom supervised, unsupervised, and deep learning models for classification, scoring, ranking, and anomaly detection, trained on your data and benchmarked against a baseline you agree to upfront.
Computer Vision Development
Object detection, OCR and document parsing, quality inspection, and video analytics, deployed to cloud or edge devices.
Natural Language Processing Development
Entity extraction, classification, summarisation, sentiment analysis, semantic search, and multilingual text pipelines.
Predictive Analytics and Forecasting
Demand, churn, revenue, and risk forecasting models wired into dashboards your team already uses.
AI Integration and API Development
AI capability added to the product you already run. We integrate with your existing stack, CRM, ERP, data warehouse, and internal tools through clean, documented APIs.
MLOps, Deployment and Model Monitoring
CI/CD for models, versioning, drift detection, evaluation pipelines, cost monitoring, and retraining workflows, so the system stays reliable after handover.
Not sure which of these you actually need?
Most teams arrive with a tool in mind and leave with a better use case. Bring the outcome you want. We will tell you the shortest technical path to it, including when the answer is that you do not need a custom model at all.
Three ways to work with our AI development team
Pixel Web Solutions offers three AI development engagement models: a fixed-scope AI build, a dedicated AI development team, and a managed AI product partnership.
Fixed-scope AI build
Best for
Validating one use case fast
You get
Defined deliverable, fixed price
Typical duration
4 to 10 weeks
You bring
A use case and sample data
Commercial model
Fixed fee per milestone
Dedicated AI team
Best for
Ongoing roadmap, in-house PM
You get
Engineers embedded in your sprints
Typical duration
3 months and up, rolling
You bring
Product ownership
Commercial model
Monthly per engineer
Managed AI partner
Best for
No internal AI capacity
You get
Strategy, build, run, and support
Typical duration
6 months and up
You bring
The business goal
Commercial model
Monthly retainer
A proven AI development process, from data to deployment
Our AI development process runs in six stages: discovery and feasibility, data readiness, architecture and model selection, build and evaluation, deployment and integration, then monitoring and retraining.
Discovery and feasibility
week 1 : We define the business outcome, the success metric, and the baseline to beat. You get an honest feasibility call, including the cases where a rules engine beats a model.
Data readiness and architecture
weeks 1 to 2 : We audit data volume, quality, labelling, and access rights, then design the pipeline, storage, and system architecture. Deliverable: a technical blueprint and a data gap list.
Model selection and prototype
weeks 2 to 4 : We choose between a hosted foundation model, an open-weight model, RAG, fine-tuning, or a custom-trained model, based on accuracy, latency, cost per request, and data sensitivity. Deliverable: a working prototype on your data.
Build, evaluate, and harden
weeks 4 to 8 : Full application build with an evaluation harness, golden test sets, guardrails, fallback behaviour, and red-team prompts. Deliverable: measured accuracy against the agreed baseline.
Deployment and integration
weeks 8 to 10 : Deployment to your cloud or ours, integration with existing systems, access control, logging, and user acceptance testing. Deliverable: a live system and full documentation.
Monitor, retrain, and scale
Drift detection, cost monitoring, feedback capture, scheduled retraining, and roadmap for the next use case. Deliverable: a running system with an owner, whether that owner is your team or ours.
Find out if your data can support the AI system you want, before you spend on it
A 30-minute AI feasibility check covering your use case, data readiness, model options, realistic cost band, and timeline. No obligation, no pitch deck.
- Senior engineer, not a salesperson
- Written summary within 48 hours
- Honest no when the answer is no
Why Choose Pixel Web Solutions as Your AI Development Company
Model-agnostic by design
We are not resellers for any model provider. We benchmark options against your accuracy, latency, and cost per request, then recommend the cheapest option that clears the bar.
Production engineering, not lab work
Our AI engineers ship inside real product teams alongside web, mobile, and blockchain engineers, so the model lands in a working application rather than a notebook.
You own everything
Full IP transfer on code, prompts, fine-tuned weights, evaluation sets, and documentation. No lock-in to a proprietary Pixel platform.
Cost control from day one
Token cost, inference cost, and infrastructure cost are modelled before the build, monitored after launch, and optimised through caching, routing, and smaller models where quality allows.
Security and compliance built in
Data handling aligned to GDPR, with HIPAA and SOC 2 aligned workflows available for regulated builds. Private deployment and self-hosted open-weight models where data cannot leave your environment.
Support that outlasts the invoice
Post-launch monitoring, retraining, and an SLA-backed support window on every engagement. Confirm your standard SLA tiers before publishing.
Industry-specific AI development services
We build AI systems for regulated and data-heavy industries where accuracy, auditability, and integration matter more than novelty.
| Industry | What we build |
|---|---|
| Healthcare | Clinical documentation assistants, triage support, medical document extraction, patient engagement agents |
| Fintech and banking | Fraud detection, credit risk scoring, KYC document automation, transaction categorisation |
| Ecommerce and retail | Recommendation engines, demand forecasting, catalogue enrichment, support agents |
| Logistics and supply chain | Route and ETA prediction, warehouse vision systems, document automation |
| Real estate | Property matching, valuation models, lease and contract extraction |
| Manufacturing | Visual quality inspection, predictive maintenance, yield optimisation |
| Education | Adaptive learning engines, automated assessment, content generation |
| Media and marketing | Content generation pipelines, asset tagging, audience modelling |
| Web3 and blockchain | On-chain analytics, smart contract risk scoring, AI-assisted trading and compliance tooling |
Healthcare caveat : clinical decision support requires regulatory review, and we scope those builds with your compliance team from the first call.
High-value AI use cases we deliver
Document intelligence
Extract structured data from invoices, contracts, claims, and scanned records with human review on low-confidence outputs. Typical outcome: manual processing time cut sharply on high-volume document workflows.
Customer support agents
RAG-grounded agents that answer from your documentation, take actions in your systems, and escalate cleanly to a human with full context.
Demand and revenue forecasting
Time-series models that account for seasonality, promotions, and external signals, delivered into the dashboard your team already uses.
Recommendation and personalisation engines
Real-time product, content, and offer ranking based on behavioural and catalogue data.
Fraud and anomaly detection
Streaming models that score transactions and events in real time with explainable outputs for compliance review.
Computer vision quality control
Defect detection on production lines, deployed to edge hardware for low-latency inspection.
Models, platforms and frameworks we build on
We select the stack per project. These are the systems our AI development team works with in production.
Foundation models :
Frameworks :
Vector and data :
Cloud and MLOps :
Tools and Technologies We Use
Languages
ML and deep learning
LLM tooling
Vision
NLP
Vector databases
Data engineering
MLOps
Cloud
DevOps
Application layer
AI development work that produced measurable results
Faster Document Processing
Document processing time reduced by 72% for a healthcare client after deploying an AI-powered extraction pipeline, measured over 6 months.
Faster Support Resolution
Customer-support resolution time improved by 58% for a fintech client following the implementation of an AI assistant, measured across 85,000 support interactions over 6 months.
Lower Operational Costs
Operational costs reduced by 34% for a retail & e-commerce client after automating inventory management and order processing with a custom AI workflow, measured over 9 months.
AI development services vs AI consulting services
AI consulting services define what to build and whether it is feasible. AI development services build, deploy, and maintain the system. Most engagements need both, and we deliver them together or separately.
| AI consulting services | AI development services | |
|---|---|---|
| Core question answered | Should we build this, and what is the ROI? | How do we build it and run it? |
| Main deliverable | Roadmap, feasibility report, architecture, business case | Working, deployed AI system |
| Typical duration | 2 to 6 weeks | 6 weeks to 6 months |
| Team | Strategist, solution architect, data advisor | AI/ML engineers, data engineers, backend and frontend developers, DevOps |
| Output owned by you | Documents and decisions | Code, models, prompts, pipelines, documentation |
| Best starting point when | Multiple use cases, unclear priority, board buy-in needed | Use case is clear and data exists |
| Ends with | A decision and a plan | A live system and a retraining plan |
Not sure where to start? If you're still evaluating AI opportunities, begin with our AI consulting services. If you already have a defined use case, book a 30-minute AI scoping call, and we'll recommend the fastest path to deployment.
How much do AI development services cost?
AI development costs depend on data readiness, model approach, and integration depth. A proof of concept typically runs a few weeks at a fixed fee, a production MVP takes 2 to 4 months, and an enterprise-grade system with compliance and MLOps runs longer. We quote a fixed band after the free scoping call, before any commitment.
| Engagement | Scope | Typical timeline |
|---|---|---|
| Proof of concept | One use case, sample data, feasibility proof | 3 to 5 weeks |
| Production MVP | Live system, real users, evaluation and monitoring | 2 to 4 months |
| Enterprise AI build | Multi-use case, compliance, MLOps, integrations | 4 months and up |
Fixed price per milestone. No open-ended hourly billing on scoped builds.
Book your free AI development consultation
Tell us what you want AI to do in your business. In 30 minutes, a senior AI engineer will map your highest-value use case, flag the data gaps, and give you a realistic cost and timeline band.
- A prioritised, high-value AI use case for your business
- An honest view of feasibility, data readiness, cost, and timeline
- Clear next steps, whether or not you work with us
- We reply within one business day.
Prefer email? Send your brief to : sales@pixelwebsolutions.com
Frequently asked questions
Ready to build your first AI system?
Tell us the outcome. We will map the shortest technical path to it, and give you a realistic view of cost, data, and timeline before you commit to anything.
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