Knowledge assistant
Search policies, contracts, procedures and manuals, with answers traced to their sources. Measured by search time and correctly sourced answers.
Artificial intelligence
Select AI use cases by value, data availability and risk, and deliver them with the controls your organisation requires.
ATAM selects AI use cases by expected value, data availability and risk. The aim is better-informed decisions and fewer manual tasks.
Solutions combine a secure knowledge assistant, document processing, process agents, forecasting and anomaly detection, computer vision and digital twins, with the access controls and approvals each organisation requires.
Each use case is paired with an indicator, so value is measured rather than assumed.
Search policies, contracts, procedures and manuals, with answers traced to their sources. Measured by search time and correctly sourced answers.
Invoices, supplier files, forms and meeting records: OCR, classification, field and table extraction, consistency checks against ERP data and human review of exceptions. Measured by time per file and correction rate.
Prepare files and follow up exceptions and requests under business controls. Measured by tasks completed and escalations required.
Demand, inventory, cash flow and operational deviations, compared with a baseline method. Measured by forecast error and relevant alerts.
Visual inspection, counting and quality control. Measured by precision and false positives.
Asset modelling and scenario simulation, with the assumptions behind each scenario made explicit. Measured by better decisions and the gap between simulation and reality.
Conversational access to authorised information, with verifiable answers. Deliverables: qualified corpus, selected connectors, integrated assistant, evaluation report and operating guide.
Internal documents, knowledge bases and business applications, with indexing, metadata, source versions and planned updates.
RAG retrieves relevant passages before generating an answer. The assistant cites its sources and flags when information is insufficient.
Document permissions apply to both search and answers, so confidential information remains within its authorised scope.
Representative test questions in Arabic, English and French as needed, to measure relevance, accuracy, appropriate refusals, latency and cost per query.
Automate repetitive work while retaining control of sensitive decisions. Indicators: completed tasks, justified blocks, correction rate and time saved after review effort.
Each agent has a limited objective, authorised tools and business context, such as preparing a request, checking a file or suggesting an action.
Access through a dedicated service account with volume, time and spending limits. Every action remains observable and attributable.
Mandatory human approval for payments, commitments, deletions and critical changes, with escalation of conflicts, uncertainty or missing data.
Protection against malicious instructions embedded in documents, tested tools and logged execution, with controlled stopping and recovery.
Production readiness depends on clear acceptance criteria, not just a successful demonstration. Each stage ends with an explicit gate.
Use case, users, value, constraints and risks. Gate: sponsor, business owner and baseline indicator.
Data rights and quality, samples, and separation of training and test data. Gate: usable data and a representative evaluation set.
Prototype, integration and access controls. Gate: documented business, security and performance tests.
Limited use with error observation. Gate: target thresholds met and exceptions controlled.
Monitoring, costs, versions and support. Gate: a service owner and a rollback procedure.
Drift monitoring and periodic reassessment. Gate: a decision to retain, modify or retire the model.
Controls are part of the design from the start, not added afterwards.
A business workshop to define priorities, solution scope and measurable results.