AI agents
Agents that carry out multi-step tasks across your CRM, email, ERP and internal tools, with approvals for anything sensitive.
AI implementation
AI implementation services
We take AI from a promising demo to a system your team uses every day: connected to your data, built into your workflows, measured, governed and supported.
Overview
Many AI pilots never reach production. Yours should.
Almost every business has tried a chatbot or a model in a sandbox. Far fewer have AI running inside the work that matters: answering customers, processing documents, preparing reports or helping teams find information in seconds.
The gap is rarely the model. It's the work around it: reliable access to the right data, integration with the tools people already use, a way to measure whether answers are correct, controls that satisfy security and legal teams, and a rollout that people trust.
AnAInfo is an AI implementation partner for companies in the United States, the United Kingdom and Europe, and the UAE. We help you choose the use cases worth doing, build them properly, and keep them working after launch.
- Model-agnostic: we choose the model per use case
- Built on your cloud, or ours, with regional hosting
- Evaluation and monitoring from day one
- You own all code, prompts and data
What we implement
AI solutions we put into production
Knowledge assistants (RAG)
Answers from your policies, contracts, manuals and tickets, with citations so people can check the source.
Customer support AI
Assistants on your website, app or WhatsApp that resolve common requests and hand over to people with full context.
Document processing
Read invoices, claims, contracts and forms, extract the data, check it and post it to your systems.
AI inside your product
Search, summaries, writing help and recommendations built into your SaaS or mobile app.
Analytics & forecasting
Machine learning for demand, churn, risk and pricing, explained in terms your team can act on.
Internal copilots
Assistants for sales, finance, HR and engineering that draft, summarise and look things up for staff.
Workflow automation
AI steps inside existing processes, such as triage, classification, routing and quality checks.
Why AI projects stall
The problems we plan for from the start
We have seen the same issues stop AI projects in many organisations. Each one is solvable if it's addressed early, so our process deals with them before they become blockers.
- No clear owner or measurable goal for the use case
- Data that is scattered, out of date or locked behind permissions
- Demos judged on a handful of hand-picked questions
- Security and legal review left until the end
- Usage costs nobody modelled before launch
- Staff who don't know when to trust the output
How we work
Our AI implementation process
- 01
Use-case discovery
Workshops with your team to list where AI could help, then score each idea on value, feasibility, data and risk.
- 02
Data readiness
We check the documents, databases and APIs the use case needs, and fix access, quality and privacy gaps.
- 03
Proof of concept
A working prototype on your real data within weeks, tested against examples your team agrees are correct.
- 04
Evaluation
An evaluation set that measures accuracy, safety and cost, so decisions are based on evidence rather than demos.
- 05
Production build
Integration with your systems, single sign-on, permissions, audit logs, guardrails and human approval steps.
- 06
Governance & compliance
Risk assessment, documentation and controls mapped to the rules in your markets.
- 07
Rollout & training
A staged launch with the people who will use it, plus training and clear guidance on when to trust the output.
- 08
Monitor & improve
Dashboards for quality, usage and cost, with regular reviews as models and your needs change.
Included
What every implementation includes
Security review
Least-privilege access, secrets management and protection against prompt injection.
Evaluation set
Real examples with agreed answers, re-run before every release.
Guardrails
Topic limits, output checks and human approval for sensitive actions.
Observability
Logs of inputs, outputs, tool calls and costs, with privacy controls.
Cost control
Model routing, caching and budgets so running costs stay predictable.
Documentation
Architecture, data flows and risk records your auditors can read.
Training
Short sessions and guides for the people who will use the system.
Handover
Full source code, prompts and infrastructure as code, owned by you.
Governance
Responsible AI, designed in
AI rules differ by market and keep changing. We map your use case to the frameworks that apply and build the controls into the system, working alongside your legal and compliance advisers.
EU AI Act
Risk classification, transparency notices, human oversight and technical documentation for AI used in the EU.
GDPR & UK GDPR
Lawful basis, data minimisation, impact assessments and safeguards for automated decisions.
NIST AI RMF
The US framework for mapping, measuring and managing AI risk, used by many American enterprises.
ISO/IEC 42001
The international standard for AI management systems, for organisations that want certification.
UAE PDPL & free zones
The UAE's federal data law and the DIFC and ADGM regimes, including DIFC rules for autonomous systems.
Sector rules
HIPAA for US health data, DORA for EU financial services, and regulator guidance in your industry.
Technology
Models, platforms and tools
Engagement models
Work with us the way that suits you
Fixed price
For projects with a clear scope. We agree features, timeline and cost up front, and deliver in milestones you sign off one by one.
Time & material
For products that will evolve. You pay for the hours worked, with full visibility through weekly reports and a shared task board.
Dedicated team
Developers, designers and testers who work only on your product, managed by you or by our project manager.
Where we work
AI implementation for the USA, Europe and the UAE
Each market has its own rules for data and AI. We design for them from the first workshop, and plan calls in your working hours.
United States
AI agents, RAG assistants and automation for US companies, designed around the NIST AI RMF, state AI laws, HIPAA and SOC 2 controls.
Europe & UK
AI for UK and EU businesses built for the EU AI Act and GDPR, with EU data hosting and multilingual assistants.
UAE & Middle East
Arabic and English AI for Dubai, Abu Dhabi and the GCC, built for the PDPL, DIFC and ADGM rules and UAE data residency.
Guides
Read before you start
AI implementation roadmap
The seven steps from first idea to a system people rely on.
What drives AI implementation cost
Where the budget goes, and how to keep running costs predictable.
RAG vs fine-tuning
Two ways to teach a model about your business, and when to use each.
EU AI Act checklist
What providers and deployers of AI need to do, step by step.
AI rules in the USA
Federal guidance, state laws and sector rules that shape US AI projects.
Implementing AI in the UAE
National strategy, data laws, free zones and Arabic language AI.
AI implementation FAQs
What does an AI implementation partner do?
We help you pick the AI use cases worth doing, prepare the data, build and integrate the solution, test it properly, put governance in place and support it after launch. The goal is a system people use every day, not a one-off demo.
How long does AI implementation take?
A proof of concept on your own data usually takes a few weeks. Taking it to production with integrations, security review and training typically takes a few months, depending on the systems involved and the approvals you need.
Which AI model will you use?
We're model-agnostic. We compare leading commercial models and open-source models on your own examples, then choose for quality, speed, cost and where your data must stay. Many solutions use more than one model.
Can AI run on our own infrastructure?
Yes. We can deploy in your AWS, Azure or Google Cloud account, in a specific region such as the EU or the UAE, or use self-hosted open-source models when data must not leave your environment.
How do you stop the AI from making things up?
We ground answers in your own data, show sources, test against an evaluation set, tell the system to say when it doesn't know, and require human approval for anything with real consequences.
Do we own what you build?
Yes. Source code, prompts, evaluation data and infrastructure configuration are handed over to you.
What are you waiting for?
Let's talk about your project
Tell us what you're building, or what needs rescuing. We reply within one business day.