AI Machine Learning Services for Business
Explore our ai machine learning services that enhance efficiency and automate tasks. Contact us for tailored solutions to your business needs.
AI with numbers attached
We provide tangible proof of value using your own data before you commit to larger projects.
Typical pilot
wks
Each project is linked to key metrics that matter, such as hours saved or accuracy of forecasts.
Clear success metric
Our document assistants provide citations for each response, allowing staff to verify the information.
Answers with sources
Our assistants can respond to customers and staff at any time, transferring to a human when necessary.
Assistant availability
We ensure AI projects are transparent, measurable, and secure.
AI that addresses business challenges, not merely demonstrations.
The machine learning lifecycle consists of six stages: collect, prepare, train, evaluate, deploy, and monitor, along with privacy and review safeguards.
Artificial intelligence is now accessible for companies of all sizes, but it creates value only when directed towards the right challenges. We start every collaboration by identifying the processes where AI and machine learning can save the most time or money: repetitive questions your team answers daily, documents that are manually typed, or decisions based on intuition that data could enhance.
From there, we develop the simplest effective solution. This might be a generative AI assistant tailored to your policies and manuals. In other cases, it could be a traditional machine learning model for forecasting, classification, or anomaly detection. Frequently, it is a combination, presented through a user-friendly interface and integrated with the ERP, CRM, or website you already utilise.
Responsible by design
We ensure that stakeholders are informed during crucial decision-making, document the system's actions, establish budget constraints on AI usage, and conduct thorough tests for accuracy and bias before deployment. Your data is handled under enterprise terms or hosted models and is never used to train a public model.
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AI and machine learning services
Website and WhatsApp assistants that respond to customer inquiries using your knowledge base, transferring to a human when needed.
AI chatbots and customer support
Internal assistants that search through policies, contracts, manuals, and tickets to answer staff queries with referenced sources.
Document assistants (RAG)
Forecasts for demand, sales, and cash flow, along with churn prediction and lead scoring based on your historical data.
Forecasting and predictive analytics
Automatic extraction of data from invoices, receipts, forms, and ID documents into your ERP or accounting system.
Document processing and OCR
Image recognition for quality control, product cataloguing, counting, and attendance or access management.
Computer vision
We classify emails, draft replies, summarise reports, and route work, ensuring that approvals are integrated into the workflow.
AI workflow automation
Demonstrated use cases that provide value in months rather than years.
How we deliver AI projects
We pinpoint the processes where AI can provide the most benefit, assess the potential value of each, and agree on a success metric for the initial project.
Use case workshop
1 week
We gather, clean, and secure relevant data. For assistants, we organise, chunk, and index documents; for models, we engineer features.
Data preparation
1 to 3 weeks
We develop a working pilot using your actual data, evaluated against the agreed metric, ensuring that the decision to scale is based on solid evidence.
Proof of value
2 to 4 weeks
The pilot evolves into a comprehensive service, complete with an interface, APIs, integrations, access control, logging, cost limits, and human review when necessary.
Production build
4 to 10 weeks
We assess accuracy, edge cases, bias, prompt injection, and data leakage, while documenting the appropriate and inappropriate uses of the system.
Evaluation and safety
Before launch
We monitor quality, usage, and costs in production. Models are retrained and knowledge is updated as your business and data evolve.
Monitor and improve
Ongoing
We take small, measurable steps that demonstrate value early and manage risk effectively.
AI models, tools and platforms
We utilise leading commercial and open models, selected based on specific use cases.
Language models
Grounding answers in your own knowledge.
Retrieval and search
Classic ML where it beats a language model.
Machine learning
Turning images and paper into data.
Vision and documents
Running AI reliably in production.
MLOps and integration
We are model-agnostic, selecting the best option based on accuracy, cost, and privacy considerations.
Assistants that answer from your own knowledge
Retrieval-augmented generation: your company documents transformed into embeddings, enabling a language model to provide answers with citations.
A general chatbot has a broad understanding of various topics but lacks knowledge about your specific business. Retrieval-augmented generation (RAG) addresses this issue. Your policies, product manuals, standard operating procedures, and past tickets are indexed securely, ensuring that every response is generated from the relevant passages that directly relate to the question.
- Cited answers: each response references the document and section from which it originated.
- Permission-aware: staff only receive answers from documents they are authorised to access.
- Always current: newly created or updated documents are re-indexed automatically.
- Safe fallbacks: if the answer is not found in your documents, the assistant will inform the user and direct the question to a human.
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How AI is already benefiting businesses
Receive instant answers to routine queries around the clock, with a smooth transition to agents for more complex issues.
Customer service
Capture invoices and receipts, categorise expenses, assist with reconciliation, and forecast cash flow.
Finance and accounts
Forecast demand, suggest reorders, predict delivery times, and alert you to anomalies in stock and orders.
Operations and supply chain
Score leads, predict churn, recommend products, and generate initial drafts for your marketing campaigns.
Sales and marketing
Provide staff with a policy assistant, support CV screening, and streamline onboarding with a searchable knowledge base.
HR and internal teams
Conduct visual inspections, check documents against established rules, and summarise lengthy reports for reviewers.
Quality and compliance
Common starting points, organised by the teams that benefit.
Start your AI journey the right way
AI discovery workshop
A targeted workshop to identify, size, and prioritise AI opportunities in your business, culminating in a practical roadmap.
Teams exploring what is possible
A targeted workshop to identify, size, and prioritise AI opportunities in your business, culminating in a practical roadmap.Book a workshop
Proof of value pilot
Develop a working pilot using your own data within weeks, measured against agreed metrics before further investment.
Best first step
One clear, high-value use case
Develop a working pilot using your own data within weeks, measured against agreed metrics before further investment.Start a pilot
Production AI solution
A secure, monitored AI service integrated with your systems, complete with training, documentation, and ongoing enhancements.
Scaling a proven use case
A secure, monitored AI service integrated with your systems, complete with training, documentation, and ongoing enhancements.Scale my AI
Begin your AI journey on the right path.
AI and machine learning: frequently asked questions
The most effective outcomes arise from consistent, data-intensive tasks: responding to frequent customer and staff inquiries, extracting information from documents, predicting demand or cash flow, categorising emails and tickets, and identifying unusual transactions. A brief discovery workshop will help determine which of these tasks are relevant to your organisation and their potential value.
What types of challenges can AI address for my business?
Yes, when configured correctly. We utilise enterprise AI services that do not train on your data, or self-hosted open models when your data needs to remain on your own servers. Access is managed through permissions, and every request is documented.
Is our company data secure when using AI?
The requirements vary based on the task. Document assistants can manage a manageable collection of well-organised documents. Forecasting typically requires one to two years of consistent historical data. We evaluate data readiness at the outset and provide you with an honest assessment of whether additional data is necessary.
How much data is required for machine learning?
Retrieval-augmented generation enables a language model to provide answers based on your own documents instead of relying solely on general internet knowledge. This approach minimises the occurrence of inaccurate responses, ensures that each reply can reference its source, and allows for updates without the need to retrain the model.
What is RAG and why is it significant?
A proof-of-value pilot generally takes between 2 to 4 weeks, provided the necessary data is available. Transforming a successful pilot into a production system, complete with integrations and monitoring, typically requires an additional 4 to 10 weeks.
How long does an AI project take?
Yes. Contemporary language models effectively manage both Urdu and English, including mixed Roman Urdu. Additionally, OCR technology can accurately read printed documents in both languages. We assess quality based on the languages your customers and staff genuinely use.
Can AI operate in Urdu as effectively as in English?
Based on our experience, AI functions most effectively as an assistant. It handles repetitive tasks, allowing your team to concentrate on judgement, building relationships, and managing exceptions. We create workflows that incorporate human review in areas where accuracy is crucial.
Will AI replace our employees?
We select the most economical model for each task, cache recurring work, establish usage limits and alerts, and provide reports on cost per request, ensuring that your AI expenditure remains predictable as usage increases.
How can you manage the running costs of AI?
Clear answers for business leaders considering AI.
Contact an engineer directly via email, phone, or WhatsApp for a straightforward answer, not a sales pitch.
Still have a question?
Talk to our team
Let us find your first AI win
Share with us the repetitive tasks, documents, or decisions where you need assistance. We will propose a use case, outline the necessary data, and provide a practical pilot plan.
Share with us the repetitive tasks, documents, or decisions where you need assistance. We will propose a use case, outline the necessary data, and provide a practical pilot plan.Explore an AI use case
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