Enterprise AI · Singapore HQ · APAC & Middle East
Turn enterprise knowledge, documents and repeatable workflows into practical AI applications. We scope the use case, connect it to your systems and agree how quality, security and business value will be evaluated.
These are possible engagement scopes, tailored to your data, users and operating requirements. Outcomes are evaluated against an agreed baseline.
Help employees find answers across approved policies, manuals and knowledge sources, with references back to the underlying material.
What to scope
Knowledge-source assessment, retrieval workflow and a representative answer-quality evaluation.
Extract, classify and summarise information from business documents. Route uncertain or consequential outputs to an authorised reviewer.
What to scope
Agreed document types, extraction fields, review rules and sample-based validation.
Answer supported service questions, guide users to the right next step and hand off to a team when the answer needs human judgement.
What to scope
Approved knowledge, conversation boundaries, escalation routes and response-quality checks.
Connect AI outputs to existing applications through agreed interfaces. Define permissions and approval steps before enabling any action.
What to scope
Integration scope, access boundaries, exception handling and test evidence.
Organise unstructured information through classification, summarisation and analysis so teams can review it more efficiently. People retain responsibility for consequential decisions.
What to scope
Defined categories, evaluation data, review criteria and documented limitations.
Prioritise a viable use case before committing to a wider rollout. Assess data readiness, integration needs and the evidence a pilot must produce.
What to scope
Prioritised scope, success measures, dependencies and a proposal for the next stage.
Our technology relationships support client solutions built with OpenAI, Anthropic Claude and IBM technologies. We select the model and platform around the task, evaluation results, integration needs and commercial requirements.
Build applications using OpenAI models for enterprise knowledge, document and conversational workflows.
Build client solutions using Anthropic Claude models for document, knowledge and workflow applications.
Implement AI solutions using IBM’s enterprise technology ecosystem, including watsonx where appropriate.
The proposal confirms the provider, model access, licensing, hosting and data-processing terms for your engagement.
Agree the business owner, users, workflow, data sources and measurable success criteria. Identify constraints before choosing the architecture.
Define model and retrieval choices, integrations and review controls. Test a representative sample and document quality and failure cases.
Implement the agreed application and interfaces. Validate functionality, permissions, security requirements and user acceptance.
Agree release approval, operational ownership, monitoring, handover and support scope. Review changes to models, data and workflows through an agreed process.
For enterprise and public-sector evaluation, establish these requirements with your business, IT, security and procurement teams before production use.
Identify permitted data, source owners, access controls and retention requirements. Confirm residency and provider-processing arrangements for the proposed deployment.
Use representative evaluation data and agreed thresholds. Define source references, uncertainty handling and the decisions that require human approval.
Set logging, monitoring, escalation and change responsibilities. Document known limitations, support arrangements and handover requirements.
Confirm the contracting entity, statement of work, deliverables, client dependencies, acceptance criteria and ongoing provider or infrastructure costs.
An accountable business owner, authorised sample data, subject experts and the relevant system, security and procurement requirements. Start with the workflow and desired outcome; share confidential material directly with the team.
Vetta applies AI to hiring workflows, including resume parsing, skill extraction, intelligent shortlisting and review support. Built in Singapore for regulated industries, it is currently in private pilot. Discuss current features, demonstration access and deployment requirements with the product team.
Explore Vettavetta-ai.com
nSearch Technologies is the group’s dedicated AI and digital solutions arm. The team confirms the appropriate contracting and delivery entity for each engagement.
Meet nSearch Technologiesnsearchtech.com
nSearch is an OpenAI Select Partner, a member of the Claude Partner Network and an IBM Silver Partner. We build client solutions using these model and technology ecosystems. Platform selection and access are confirmed against the use case, evaluation results and engagement requirements.
An engagement can include approved enterprise knowledge sources and application interfaces. Discovery confirms data ownership, quality, permissions, integration feasibility and any restrictions. Do not send confidential documents through the website assistant; discuss an authorised sharing route with the team.
Quality targets, human review, residency, hosting and provider-processing terms must be defined and evaluated for the proposed solution. AI outputs can be wrong, so acceptance uses representative testing and agreed controls. This page does not promise a universal accuracy percentage or hosting arrangement.
Pricing is scoped during proposal and solution design, based on the workflow, data preparation, integrations, evaluation, deployment and support requirements. Model usage and infrastructure costs should be identified in the proposal. Share your requirements to discuss the appropriate scope.
Tell us who will use the solution, the information it needs and the outcome you want to measure. We will discuss a practical scope and next steps.
Click to chat. Drag to move, or use the arrow keys when focused. Home resets the position.
