Answer employee questions
from your company's data

AI agents for mid-sized companies answer employee questions from SharePoint and other company sources, with citations people can open and check.

An AI agent platform for mid-sized companies

Build, run, and improve agents in one place.

Build

Design AI workflows with knowledge sources, tools, triggers, and human approval steps on a visual canvas.

Operate

Run with permissions, escalation, auditability, and full visibility into how agents behave in production.

Improve

Evaluate outputs, measure groundedness, and refine agent performance continuously.

Built-in observability and control

Keep agents grounded, reviewable, and under human control as more teams start using them.

Grounded in Company Sources

Answers cite the documents, policies, and data your teams already use, so employees can check the source themselves.

Human Oversight

Critical actions route to the right person before anything is sent, changed, or executed.

Full Traceability

See which workflow ran, which sources it used, and which actions the agent took.

Roll Out in Stages

Start with one use case, measure the result, and add teams on the same governed platform.

Included with the platform

The production tools are part of the platform

AI-Flow includes document ingestion, access controls, traces, cost tracking, feedback, and evaluation. The product screenshots below show how each part works.

Build

A visual builder your whole team can read

The visual canvas shows each agent's knowledge, tools, triggers, and approval steps. Business experts can follow the logic, while technical colleagues configure the details.

The AI-Flow builder showing an agent with its tools and triggers
Documents

Document ingestion that handles a real SharePoint

Sync SharePoint folders continuously, upload files, or pull from the web. Search every knowledge base by keyword, semantically, or both, and edit documents in place with a built-in editor.

Document Manager syncing a SharePoint folder into a knowledge base
Grounded answers

Every claim links to the page it came from

Answers cite their sources with footnotes. A click opens the sources panel with the document, the page, and the passage, so anyone can check the agent's work.

Sources panel showing the cited contract PDF next to the answer
Observability

Every run can be replayed, step by step

Call History records every execution with its trigger, duration, and cost. Open the full trace of any run or download its audit log. When a run fails, the trace shows the step where it failed.

Call History listing every agent execution with trace and audit log
Operations

Track cost by model, agent, and call

See token usage and provider-reported cost by model, agent, connection, trigger, or individual call. Cached and reasoning tokens are included in the same view.

Usage dashboard breaking down tokens and cost per model and agent
Governance

Manage users, permissions, and adoption in one place

Role-based access control, organization-wide sharing, granular permissions, and adoption analytics live in the same admin area. Export usage data to Excel for reporting.

Analytics dashboard with user engagement and adoption metrics
Feedback

A thumbs-down goes straight into the evaluation suite

Anyone can rate an answer in place, pick a reason, and add a comment. The evaluation suite collects these next to your test sets, so you find quality problems where they happen.

Feedback dialog on an answer with a reason and a comment

Also included

  • Human approval steps before critical actions
  • Agent versioning with named checkpoints and rollback
  • Publishing an agent is a click: a shareable web app with its own URL, password, or org sign-in
  • Triggers from email, Telegram, schedules, and webhooks
  • Built-in evaluation with precision, recall, and groundedness scores
  • Model-agnostic: OpenAI, Anthropic, Mistral, Gemini, and European models
Evaluation

Test answer quality before and after rollout

Use the same evaluation workspace before launch and in production. Review groundedness, failure cases, and answer quality against real scenarios.

Groundedness

Check whether answers cite approved sources, follow defined boundaries, and refuse when they should.

Quality

Score relevance, completeness, and usefulness against real scenarios before release.

Improvement

Use traces, failed cases, and evaluator feedback to decide what to change in the workflow.

The evaluation workspace scoring agents for precision, recall, and groundedness

Before rollout

Run curated scenarios that test grounded answers, refusals, escalation paths, and retrieval quality.

In production

Inspect what the agent said, what it used, and where the workflow succeeded or broke down.

Evaluation workspace

Compare prompts, agents, and RAG configurations against the same test set.

Open evaluation
Why AI-Flow.eu

What AI-Flow.eu includes

Workflow control, credential isolation, managed deployment, and evaluation in one platform.

AI Flow
AI agents with visible workflows and controls
01
Defined workflow execution
Use fixed steps where predictable behavior is required
Workflow steps you define
The agent follows the sequence you configure
Visual flow builder
Every step is explicit and auditable
Controlled execution paths
Limit model calls to the steps and tools you configure
Built-in agent services
RAG, memory, and API connections in the same platform
Built-in vector databases
Knowledge retrieval without external infrastructure
Persistent agent memory
Context that survives across sessions and users
Guided connection setup
Configure service connections in the app
02
Credential protection
Credentials stay outside model context
Credential isolation
Secrets are encrypted and excluded from the LLM context window
Encrypted secrets vault
API keys and tokens never passed to a model
Full audit trail
Every agent action is logged and traceable
Model-agnostic architecture
Works across model providers and API contracts
Change models without rebuilding
Keep the workflow structure when you switch providers
Stable workflow structure
The configured steps stay in place across model changes
03
Managed deployment
Launch without a separate infrastructure project
Managed cloud option
Run without maintaining servers or containers
Hosted deployment
AI-Flow manages the application infrastructure
Single control center
All agents, triggers, and sources in one place
Actions in connected systems
Update calendars, send email, or call business APIs from a workflow.
Calendar, email, and API connections
Run actions in the systems your teams already use
Low technical barrier
Analysts can configure workflows in the visual builder
04
Built-in evaluation
Test answer quality before and after rollout
Pre-release evaluation suite
Run repeatable scenarios before release
Automated test scenarios
Coverage across grounded answers, refusals, and retrieval
Groundedness scoring
Measure precision, faithfulness, and recall
Scheduled evaluation runs
Track quality over time with repeatable test runs
Result history
Compare groundedness and other scores across runs
Production feedback
Review ratings and comments alongside evaluation results
Hands-on

Prefer to validate it yourself first?

Open a personal agent, inspect the builder, and try the evaluation workspace before booking a demo.

Find the right AI-Flow plan for your team

See Pricing