Solution · AI agents & assistants
AI agents and assistants that do real work
We design, build and govern AI that takes on research, qualification, customer answers and drafting inside the tools your teams already use, with clear rules for when a person takes over.
The challenge
Why most AI projects stall
- Chatbots answer from generic knowledge instead of your policies and products
- Pilots never connect to CRM, helpdesk or order data
- No guardrails, so nobody trusts the output enough to use it
- No measurement, so nobody can say whether it helped
What Enkratis does
Capabilities
Each capability is designed to connect with the rest of your system, not to stand alone.
AI research agents
Summaries of accounts, contacts, orders and history before a conversation starts.
Qualification agents
Read enquiries, assess intent and fit, then route or respond accordingly.
Knowledge assistants
Answers grounded in your documents, policies and product data, with sources.
Drafting assistants
Emails, follow-ups, proposals and product copy prepared for human review.
Decision support
Flags for risk, anomalies and next-best actions inside pipelines and journeys.
Governance & evaluation
Approval steps, confidence thresholds, logging and regular quality reviews.
How it works
From first workflow to working system
What you get
Systems, deliverables and outcomes
Works across your stack
What we hand over
- AI use-case map ranked by value and risk
- Working agents or assistants connected to your systems
- Guardrails: permissions, approvals, escalation and logging
- Evaluation set and quality review routine
- Team guide and ownership handover
What it should change
- Less time spent on research, triage and repetitive answers
- Faster, more consistent responses to customers and leads
- AI your team trusts because they can see how it behaves
- A repeatable, safe way to add new AI use cases
What is the difference between an AI agent and a chatbot?
A chatbot mainly converses. An AI agent can also take actions, such as looking up records, updating a CRM, creating a ticket or triggering a workflow, within limits you define. We choose the right approach for the job.
Will AI replace our team?
That is not the goal. We use AI to remove repetitive work and speed up routine decisions, and we design clear hand-offs so people handle judgement, relationships and exceptions.
How do you keep AI accurate?
By grounding answers in your own approved data, limiting what the AI can access, testing against real examples before launch and reviewing quality regularly afterwards.
Which AI models do you use?
We select models per use case based on quality, cost, speed and data requirements, and design systems so the model can be changed later without rebuilding everything.
Next step
Find out where your growth system is leaking.
Choose the step that fits where you are today.