AI readiness assessment & strategy
Before recommending anything, we assess where your business stands — data infrastructure, technical constraints, realistic ROI by use case — and define what to build first and what to skip.
AI ideation workshop
A structured half-day to full-day working session with your team. We map your business processes, identify where automation or intelligence could save time or create new value, and prioritise ideas by impact and feasibility. You leave with a shortlist, not a whiteboard full of vague possibilities.
Problem estimation & scoping
Our AI consultants define the technical approach, data requirements, integration points, and risks before development starts. You get a phased effort and cost estimate — so you know exactly what you’re committing to before you commit.
AI data preparation & training
Good outputs depend on good inputs. We structure, clean, and prepare your datasets for model training and fine-tuning — handling the full pipeline from raw source to training-ready format.
AI model selection & implementation
The wrong model costs time, money, and trust. We evaluate options against your specific requirements — performance, latency, cost, compliance, data privacy — then implement, test, and deploy.
Custom generative AI solution development
We build applications tailored to your use case: chatbots, copilots, document analysis tools, recommendation engines, content generation systems, multimodal applications. Not generic tools bolted onto your workflow.
AI integration into existing workflows
Most projects don’t replace existing infrastructure, they extend it. We integrate into your CRM, ERP, support platform, or internal tooling with minimal disruption and full handoff documentation for your team.
Post-deployment support
We monitor performance, catch output quality issues early, retrain models as your data evolves, and release updates as your needs grow. We don’t disappear after go-live.
GPT-5
Our go-to for anything where getting it wrong is expensive. Complex reasoning, multi-step enterprise workflows, serious document analysis — when accuracy matters more than speed or cost, this is what we reach for.
Claude
If your industry has regulators, auditors, or lawyers involved, Claude is usually our first recommendation. It handles long documents without losing the thread, follows nuanced instructions reliably, and doesn’t surprise you with erratic outputs at 2am on a Friday.
Gemini
Strong when a project mixes text, images, and code in the same workflow — or when a client is already running on Google Cloud and adding another vendor relationship doesn’t make sense.
Amazon Nova (via AWS Bedrock)
For teams already deep in AWS, this is the path of least resistance. Nova 2 handles complex reasoning, gives you a 1M-token context window, and plugs straight into the infrastructure you’ve already built and secured — without the overhead of a separate API relationship.
Llama 4
When the answer to “can our data leave our environment?” is a hard no, Llama 3 is where we start. Open-weight, well-maintained, and the most battle-tested option for private cloud or on-premise deployment.
Mistral
Not every task needs the most powerful model available. For high-volume applications (classification, document triage, support automation) Mistral delivers solid results at a cost that doesn’t make the finance team nervous. And for teams with EU data residency requirements, it’s the only frontier-model provider actively building sovereign European infrastructure.
Nano Banana 2 (Google DeepMind)
Google’s image generation model, part of the Gemini family. We use it when a project needs consistent visual outputs at scale — product imagery, marketing assets, creative workflows where the same character or scene needs to look right across dozens of variations, not just one.
Phi-2
Compact and fast. Used when a full-size model would be overkill — edge deployments, lightweight classification tasks, embedded features where latency and compute cost are the binding constraints.
Whisper
The reliable choice for anything involving speech — transcription pipelines, call centre analysis, meeting summaries, voice interfaces. It handles accents and variable audio quality better than most alternatives we’ve tested.
Stable Diffusion
When a client needs image generation but their legal or security team won’t sign off on sending assets to an external API, Stable Diffusion runs on your own infrastructure. Full control, no data leaving the building.
Discovery & use case definition
We map your business goals, data sources, and technical environment to identify the highest-value starting point, not just what’s technically possible, but what’s commercially worth building first. We audit your existing data pipelines, API readiness, and operational bottlenecks to ensure the foundation is solid before a single line of code is written.
Prototyping & validation
Once we’ve agreed on the direction, we build a working prototype that demonstrates how a generative AI solution performs on your data and use case. This isn’t a static mockup — it’s a functional proof of concept you can interact with and evaluate. We then refine the models and data to optimize the results.
Development & integration
Full build: fine-tuning, backend infrastructure, API integrations, interfaces. We integrate into your existing workflow — CRM, internal tools, customer-facing platform — document everything, and make sure your team understands what we’ve built without staying dependent on us.
Deployment & continuous improvement
We deploy, configure monitoring, and set up alerting for performance drift. Then we stay involved — tracking output quality, retraining models as your data evolves, and improving results over time. A model that performs well on day one will degrade without attention. We make sure someone’s paying attention.
Cloud AI platforms
Frameworks & libraries
Data & MLOps
Developer tools & APIs
Languages
Fintech
Financial services generate more data than most teams can act on. We help fintech companies turn that into working AI systems that is compliant, auditable, and built for regulated environments.
- fraud detection and transaction monitoring
- automated KYC and document verification
- AI-powered customer support and smart routing
Edtech
Engagement drops fast when learning feels generic. We work with edtech companies to build AI that adapts to individual users and cuts manual workload for instructors and ops teams.
- adaptive learning paths and personalised content delivery
- automated assessment and feedback systems
- AI tutoring and instructor support tools
Retail
Margins are thin, and customer expectations aren’t. We help retailers apply AI where it moves the needle — conversion, retention, and back-office efficiency.
- product recommendations and personalised marketing
- AI-powered customer support and chatbots
- demand forecasting and inventory optimisation
Real estate
Property decisions involve more paperwork than insight. We help real estate companies automate document-heavy workflows and make better calls with predictive data.
- property appraisals and valuations
- predictive analytics for pricing and demand
- automated document processing and contract review
Manufacturing & Logistics
We deploy AI solutions that handle complex, data-heavy tasks that slow down manufacturing and logistics operations.
- predictive maintenance assistants
- supply chain intelligence tools
- technical documentation generators,
- anomaly detection systems
From fragmented travel requests to an AI-powered concierge platform
Geniusee partnered with a small travel company to develop an AI-powered concierge platform that integrates travel assistance and service management into a single digital environment. The MVP combines an AI-powered chatbot for travelers with an administrative platform for managing its content, users, data, and operations.
Case details
K’CIDADE Academy: How we built an AI-powered learning platform for AKF Portugal
K'CIDADE Academy is AKF Portugal's professional learning platform for civil society organizations, educators, and community leaders. Built on adaptive learning pathways, an AI virtual tutor, and a gamified progress system, it delivers personalized training to professionals working across social inclusion, education, and community development.
Case details
Scaling Edge AI & computer vision: QuantumEye real-time surveillance platform
Geniusee helped the QuantumEye AI platform that upgrades legacy CCTV with real-time detection, instant incident notifications, and decision-ready analytics.
Case details
Anatomy Financial: Automated financial management software for healthcare
Anatomy introduces an innovative solution designed to automate document processing, compare various documents and banking transactions, and handle the intricacies of physical check processing. By conducting a thorough analysis, the system identifies discrepancies between the declared prices of medical procedures and the actual amounts received by the clinic.
Case details
MartechCompose AI: Advanced content writing solution
We partnered with Compose AI to enhance their AI-powered writing platform through cloud migration, UX improvements, seamless integrations, and scalable feature development, upporting their growth from YC-backed startup to a widely adopted productivity tool.
Case details
MartechForethought: Enterprise AI agents for customer support
Forethought partnered with Geniusee to extend and integrate its AI-powered support platforms (Assist and Discover) into complex enterprise environments. We helped enhance real-time agent assistance, streamline multi-system connectivity, and deliver a unified support experience across channels. The result is a scalable AI agent ecosystem that accelerates resolution times, boosts team productivity, and powers more consistent customer experiences.
Case details
Certified AWS Partner delivering secure, scalable cloud-native solutions.
ISO-compliant processes ensuring quality, security, and reliability.
Trusted integration partner for financial data connectivity and open banking.
Team of ISTQB-certified QA engineers for world-class software testing.
Consistently rated ★5.0 by clients for reliability and delivery excellence.
Accredited partnership supporting advanced testing and continuous QA automation.
End-to-end ownership
We don’t hand you a strategy document and leave. We own the full delivery cycle — from use case definition and data preparation through model implementation, integration, deployment, and post-launch support. One team, one point of accountability.
Business-first approach
We’re not committed to any single model or cloud vendor. We recommend the solution that best fits your use case, budget, and compliance requirements, whether that’s a hosted API, an open-source model running on your infrastructure, or a fine-tuned custom model. Our starting point is always your business problem, not our preferred tech stack.
Proven delivery in regulated industries
FinTech, healthcare, edtech, and real estate aren’t forgiving of sloppy AI implementations. We’ve delivered 180+ products in environments where data privacy, compliance, and reliability aren’t optional. We know how to build AI solutions that pass security reviews and work in the real world, not just in staging.
What exactly is generative AI?
It’s a category of models that produce new content (text, images, code, audio) by learning patterns from large amounts of existing data. The practical upshot: instead of manually writing a document, building an image, or coding a function from scratch, you describe what you need, and the model generates it. The quality and reliability of that output depend heavily on the model, the data it was trained on, and how well the solution was implemented.
What are some examples of generative AI?
GPT-5 handles text — drafting, analysis, reasoning, and code. Nano Banana 2 generates and edits images from text prompts. Whisper transcribes speech. Stable Diffusion produces visuals on private infrastructure. These aren’t novelties anymore — they’re production tools running inside real business workflows at companies across every major industry.
How can generative AI development be used in a business context?
It depends on your business. The most common applications we see are document processing, customer support automation, internal knowledge tools, content generation at scale, and data analysis.
The less common but often higher-value ones tend to be industry-specific — fraud pattern detection in fintech, adaptive learning in edtech, predictive maintenance in manufacturing. The use cases worth pursuing are those that map to a real operational bottleneck, not those that look impressive in a demo.
How can generative AI consulting help if I can just use the tools directly?
The tools are accessible. Knowing which one fits your data, your compliance requirements, and your existing infrastructure, and then building something production-ready rather than a prototype that never ships, is where most companies get stuck. We’ve seen the same failure patterns enough times to know where projects go wrong, and our job is to help you avoid them.
Can generative AI consulting help my company streamline processes, enhance productivity, or improve customer experiences?
Absolutely, generative AI consulting can significantly streamline processes, enhance productivity, and improve customer experiences across your company. By automating tasks, providing data-driven insights, and enabling personalized interactions, generative AI can optimize operations, freeing up resources and delivering a more tailored and efficient experience for both your team and customers.
What’s the future of generative AI?
Shorter model release cycles, better reasoning, lower inference costs, and tighter integration into existing software products — that’s the near-term trajectory. The more important shift is that the question is moving from “can we build this?” to “should we, and how do we govern it responsibly?”
Companies figuring out the governance side now will be in a significantly better position than those treating it as someone else’s problem.
