AI Engineering, Data Engineering & Managed Data Services
We help businesses prepare their data, build AI-powered systems, automate operations and manage them in production.
Division 1
AI Solutions
Working AI applications built and integrated into your business processes.
- 01
AI agents and workflow automation
Sales qualification, customer-support agents, appointment scheduling, order processing, CRM updates and approval-based workflows.
- 02
Enterprise AI assistants and knowledge search
Assistants that answer from your documents, products and policies, with source references, permissions and knowledge updates.
- 03
Voice AI and conversational AI
Inbound and outbound voice agents, multilingual assistants, WhatsApp bots, call summaries and contact-centre integrations.
- 04
Intelligent document processing
Extract data from invoices, purchase orders, forms and contracts, validate it, review exceptions and push it into business systems.
- 05
Model customisation and fine-tuning
Adapt existing models to your domain, language and response format, with prepared datasets and measured improvements.
- 06
Predictive AI and machine learning
Demand forecasting, churn prediction, lead scoring, recommendations, anomaly detection and inventory forecasting.
- 07
Computer vision and multimodal AI
Product-image classification, defect inspection, visual document understanding and systems combining images, text and audio.
Division 2
Data Engineering & Analytics
We turn fragmented business data into reliable, analytics-ready and AI-ready data.
- 08
Data collection and extraction
Client-authorised web extraction, API ingestion, licensed datasets, document extraction and recurring data feeds.
- 09
Data cleaning, enrichment and quality
Deduplication, standardisation, entity matching, record enrichment and validation rules.
- 10
Data pipelines and integration
Automated batch and real-time data movement between CRM, ERP, databases and analytics systems.
- 11
Data platforms and migration
Warehouses, lakes and lakehouses, legacy-data conversion, reconciliation and platform consolidation.
- 12
Analytics and business intelligence
Management dashboards, customer analytics, sales reporting and agreed definitions for business KPIs.
- 13
Knowledge engineering
Document classification, taxonomies, knowledge graphs and searchable knowledge bases prepared for AI retrieval.
Division 3
AI Data & Evaluation
Training data, expert review and measurable evaluation for AI teams and businesses customising AI.
- 14
Data annotation and labelling
Text classification, entity tagging, bounding boxes, segmentation, video tracking and document-field labelling.
- 15
Speech and multilingual datasets
Consented speech collection, transcription, speaker labels, timestamps and code-mixed language datasets.
- 16
LLM training and preference datasets
Question-answer pairs, instruction examples, corrected responses and human rankings of model outputs.
- 17
Coding and AI-agent datasets
Code-review examples, bug-fix tasks, verified unit tests and tool-use records from authorised repositories.
- 18
Synthetic data creation and validation
Generated examples, rare-case scenarios and simulated conversations with quality and duplication checks.
- 19
AI evaluation and benchmarking
Task-specific test sets, model comparisons, factuality and instruction-following checks and agent task-success testing.
- 20
Managed annotation operations
Annotation guidelines, reviewer training, quality audits, disagreement resolution and versioned secure delivery.
Division 4
AI Infrastructure & Managed Operations
We run the systems after the build: deployed, monitored, governed and maintained.
- 21
MLOps and LLMOps
Deployment, prompt and model versioning, automated evaluations, monitoring, release controls and rollback.
- 22
Private AI deployment and inference optimisation
Models in your cloud or infrastructure, with access controls, capacity planning, latency testing and cost optimisation.
- 23
AI security and governance engineering
AI-system inventories, access restrictions, audit trails, retention controls and human-approval mechanisms.
- 24
Managed data services and data products
Recurring data refreshes, pipeline support, quality monitoring, maintained datasets and licensed data APIs.
Start with a defined package
Repeatable engagements with clear deliverables, instead of an open-ended AI project.
AI & Data Readiness Assessment
Workflow review, data audit, ranked use cases, risks and implementation scope.
Fixed-fee assessment
AI Automation Implementation
One defined workflow, required integrations, evaluation and production handover.
Milestones plus maintenance
AI-Ready Data Foundation
Connected sources, cleaned data, pipelines, documentation and quality checks.
Implementation plus managed operations
Training Dataset Delivery
Agreed dataset, annotation guide, quality report and versioned export.
Paid pilot, then accepted batches
AI Evaluation & Optimisation
Baseline results, failure analysis, improvements and repeatable regression tests.
Initial audit plus recurring evaluation
Data access, permitted usage, client ownership, retention and secure handling are agreed in every project scope. Infrastructure, model usage, licensed data and specialist reviewers are itemised in proposals.