AI AGENTS AND ASSISTANTS / UNITED KINGDOM
Assistants that know your business. Agents that stay within their limits.
AI agent and assistant development for UK businesses: internal and customer-facing assistants grounded in your knowledge, and agents that complete multi-step tasks in your systems with defined permissions and human oversight.
UK-registered company. International engineering team.01 / THE OPPORTUNITY
AI agents and assistants for UK businesses.
An assistant answers. An agent acts. Both are only useful when they know your business and stay inside the lines you draw. Krapton builds AI assistants grounded in your documents and systems, and AI agents that carry out multi-step tasks such as triaging enquiries, preparing quotes, updating records or drafting responses, with permissions, approvals and audit trails designed in.
We work with models from OpenAI, Anthropic and Google, connect them to your tools through well-defined functions, and evaluate behaviour against real scenarios before release. Human review is a feature, not an afterthought.
02 / Use cases
Customer-facing assistants
Website and in-app assistants that answer from approved content and hand over to people at the right moment.
Internal knowledge assistants
Answers for staff from policies, procedures and past work, integrated with Microsoft 365, Google Workspace or Slack.
Task agents
Agents that gather information, take defined actions in your systems and ask for approval when the stakes are high.
Inbox and ticket triage
Classification, extraction, drafting and routing for shared inboxes and helpdesks.
03 / Our approach
Evaluation before release, guardrails by design and people in control of the decisions that matter.
AI development overview- 01
Define the boundary
What the assistant may answer, what the agent may do, and what always needs a person. Written down before design.
- 02
Ground and connect
Retrieval over approved knowledge and typed tool functions for actions, with least-privilege access to each system.
- 03
Evaluate against scenarios
A scenario set covering normal, edge and adversarial cases, rerun on every change.
- 04
Deploy with oversight
Confidence thresholds, approval steps, logs and dashboards so behaviour stays visible in production.
04 / Before you start
The decisions that shape the build.
Agents that act in systems need least-privilege credentials, rate limits and reversible actions. Customer-facing assistants must be clear that they are automated and must hand over when a person is needed.
What every AI engagement includes
- A use case with a measurable result and representative examples
- An evaluation set rerun on every prompt, model or data change
- UK GDPR-aware data flows, with UK or EU hosting where residency matters
- Human review and defined permissions for anything consequential
- Cost and quality monitoring after launch
05 / From the portfolio
Examples from Krapton’s international portfolio. Each success story describes the work delivered for that project.
Dental.AI
Dental.AI set out to give patients instant, AI-driven insight into their oral health from a single dental image — which meant pairing a clinical-grade analysis pipeline with a web experience patients actually trust.
Read the success storyFAQ
An assistant answers questions and drafts content from knowledge you provide. An agent can also take actions: look things up in systems, update records, send messages or run workflows, within permissions you define and with approvals where needed.
Yes. Retrieval-augmented generation indexes your approved documents and systems so answers are grounded and cited, and it can be restricted by user permissions so people only see what they are allowed to.
Least-privilege access to each tool, an explicit list of allowed actions, approval steps for anything consequential, rate limits, reversible operations where possible and full logging. We test adversarial scenarios before release.
Microsoft 365 and Teams, Google Workspace, Slack, CRMs such as HubSpot and Salesforce, helpdesks, databases and your own applications through APIs.
Quality, usage and cost dashboards, feedback capture on every answer, sampled human review and a scenario set that is rerun whenever prompts, models or data change.
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YOUR NEXT STEP
Bring the task, the examples and the systems involved. We’ll tell you what an evaluation set, a prototype and a first release would look like.