AI assistants, agents and automation

AI implementation tied to a measurable business workflow

We implement AI assistants, RAG, document workflows and agents with sources, permissions, evaluation, logs and a clear hand-off to people.

Discuss your project See starting ranges

01a defined use case, baseline and acceptance criteria before model selection

02company knowledge, tools and permissions connected with explicit boundaries

03evaluation, monitoring and human approval for risky actions

Best fit

When this service is the right starting point.

The first scope should match the real bottleneck, available evidence and the level of responsibility the implementation carries.

a support or sales team repeatedly answering from the same source material

a document process that needs classification, extraction and validation

a knowledge base that is difficult to search across roles and systems

a multi-step task where AI can prepare work but a person should keep control

Scope

A complete first stage, with clear boundaries.

Advanced integrations, migrations, unusual infrastructure and business-critical responsibility are scoped after discovery rather than hidden inside a generic package.

Use-case and risk assessment

We define users, inputs, expected output, baseline, unacceptable errors and where human review is required.

Knowledge and tool connection

We prepare sources, retrieval, permissions and the limited tools the assistant or agent is allowed to use.

Evaluation and guardrails

We build test cases, source checks, structured validation, cost limits and safe fallback behaviour.

Pilot and monitoring

We launch with a controlled group, collect feedback and monitor quality before expanding the workflow.

Delivery

Decisions made in the order that reduces risk.

Each stage produces something the team can review before the project takes on more cost or responsibility.

Choose one useful task

Prioritise a process with enough repetition, available knowledge and a result the team can evaluate.

Build the evaluation set

Collect representative questions, documents and edge cases before optimising prompts or architecture.

Implement the pilot

Connect sources and tools with narrow permissions, logs, validation and a human escalation path.

Measure and scale

Compare quality, time and cost with the baseline, then extend only the parts that work reliably.

Business outcomes

What the implementation should improve.

These are intended outcomes, not invented performance claims. The baseline and success measures are agreed for the specific project.

faster access to company knowledge with source-backed answers

less manual preparation of repetitive messages, records or documents

a visible quality process instead of relying on impressive demonstrations

safer automation because actions, permissions and human decisions are explicit

Relevant evidence

Proof and deeper context.

We link only work and solution pages that are relevant to this service and label their status honestly.

Med2Be

AI-assisted generation works inside a broader learning product with user accounts and measurable progress.

Open

Business solutions

Dedicated pages for RAG, AI agents and document automation explain the scope in more detail.

Open

FAQ

Questions before the first scope.

Direct answers about responsibility, feasibility and the way we start.

Do we need to train our own model?

Usually not. Many useful pilots combine an existing model with company sources, tools, access rules and evaluation. Fine-tuning is considered only when evidence supports it.

Can AI use private company documents?

Yes, with an architecture chosen for the sensitivity of the data, provider terms, access roles, retention requirements and the company security model.

How do you test answer quality?

We use representative test cases, source attribution, structured checks where possible and review by the people who understand the process.

Can an agent act in our systems?

It can use explicitly approved tools. Risky or irreversible actions should require validation, permissions, limits, logs and often human approval.

Related services

Connect the next layer only when the project needs it.

All services

Website strategy, UX/UI and development

Start with the problem, context and constraints.

We will help identify the smallest sensible first stage and tell you directly when the idea needs a different approach or more evidence.

Describe your project