Others talk. We orchestrate.

Your data. Your applications.
Now conversational.

Ask in plain language. Get answers from every business app you run — permission-checked, right inside Slack.
No control panel. The agent grants, revokes, and adjusts access in the conversation itself.

Let's Talk See It In Action
Most enterprises have already
adopted AI agents
40% of enterprise apps will run AI agents by year-end
— Gartner
We bridge
that gap.
Why

Others talk about AI agents.
We close the gaps between your tools.

01

"Where was that info?"

~23 min to refocus after every app switch (UC Irvine)

The deal is in HubSpot. The ticket is in Jira. The doc is in Confluence. The email is in Gmail. Your team plays detective instead of doing their job.

02

"But who should see what?"

Most AI tools skip per-user access control

Most AI tools give everyone access to everything. That's not a feature — it's a liability. Sales shouldn't see HR data. Interns shouldn't see financials.

03

"We tried ChatGPT but..."

No memory. No org context.

Generic AI doesn't know your processes, your org structure, or your data. It can't remember last week's conversation. It's a toy, not a tool.

Live Demo

See it in action

A real conversation. Multiple tools queried. Access-controlled response. Seconds.

O
One Inc
# general
# sales-team
# engineering
# product
Built for Slack — deep integration, not a generic bot
# sales-team 12
S
Sarah Chen 10:23 AM

@cleavis What's the latest on the One Inc deal? Any open tickets or blockers I should know about before my meeting at 2pm?

Cleavis APP 10:23 AM
HubSpot

One Inc — Enterprise Plan
Stage: Negotiation · Value: €240,000 · Close date: July 15
Last activity: Proposal v3 sent June 12 · Decision maker: James Wright (CTO)

Jira

2 open tickets:
P2 ONE-142 — API integration: custom webhook format needed (assigned: Dev team)
P3 ONE-155 — Onboarding documentation update (assigned: Technical Writer)

Confluence

Latest: "One Inc — Integration Proposal v3" updated 3 days ago by Mark Fischer

Financial details and margin data hidden — your role (Sales) doesn't include finance access.
3 tools queried simultaneously
Cross-referenced in one answer
Finance data hidden by RBAC
Seconds, not minutes of tab-switching
How It Works

Three steps to one conversation

01

We deploy the agent to your infrastructure

Deployed to your AWS account. Not ours — yours. Built on Bedrock AgentCore, powered by Claude. Your data never leaves.

Your AWS Account Deployed in Hours Zero Data Exposure
02

We connect your tools and configure access

MCP. A2A. REST. Whichever protocol fits — we're not locked to one. Every user authenticates individually. No shared accounts. Sales sees CRM. Engineering sees Jira. HR sees HR.

Per-User OAuth2 MCP / A2A / REST RBAC Mirroring Org Structure
03

Your team starts asking

Natural language. No commands. No training. It cross-references tools, takes action, remembers context. Answers formatted the way Slack always has — read once, act. No follow-up questions.

Natural Language Short + Long-Term Memory Action Execution Scannable, Not a Wall of Text
Two Perspectives

Built for both sides of the table

Reclaimed time is real money

Every app switch costs 23 minutes of refocus (UC Irvine research) — paid hours spent hunting for information, not closing deals or making decisions. That time goes back to the work that actually earns you money.

No vendor lock-in tax

Runs on your AWS account, not ours. No one can hold your data hostage for a price hike later — because no one but you ever has it.

You control the AI budget, to the cent

Set daily and monthly limits per person. See exactly who's using what. No surprise invoice at the end of the month — the ceiling is yours to set, not ours.

Value on day one, not after a 6-month invoice

Deployed to your infrastructure the same day. Integrations connected in days. You're not funding a 6-month consulting clock — you're paying for a working product, immediately.

Compliance mistakes cost more than software

No shared bot account. Sales sees CRM. Finance sees financials. Someone leaves? Revoke access in seconds — nobody sees what they shouldn't.

Not another pilot that dies in committee

40% of enterprise apps will run AI agents by year-end (Gartner) — yours can be one of the ones that actually ships. Live on your tools within a week. No multi-quarter evaluation, no science project.

Architecture diagram: Slack request flows through Lambda into AgentCore Runtime, which coordinates Claude, AgentCore Memory, and Knowledge Bases, passes every call through the RBAC Access Registry, then reaches business tools via MCP, A2A, or REST adapters

Protocol-Agnostic Integration

MCP, A2A (Agent2Agent), or a direct REST call — we use whichever gets your system connected without re-architecting anything. Swap or add integrations without touching agent logic. No vendor lock-in.

AWS Bedrock + AgentCore

Claude Sonnet/Opus backbone. AgentCore Runtime for orchestration. AgentCore Memory for short + long-term context. Bedrock Knowledge Bases for semantic search over your docs.

Defense in Depth RBAC

AccessRegistry in Secrets Manager. HMAC-verified, budget-gated before the model sees anything. The model never holds a credential — a trusted runtime mints per-user OAuth via AgentCore Identity and executes every call itself.

Generated code runs powerless

When the agent writes code to crunch your data, it executes in an isolated sandbox with a logs-only role — no S3, no DynamoDB, no Bedrock, no AWS access at all. Even fully attacker-controlled code has near-zero blast radius.

GDPR. AI Act. NIS2. DORA.

Data requests and deletions — automatic, full audit trail. Immutable logs, defined data flows, human oversight. One governance system satisfies them all.

It runs on your servers. We leave.

Your AWS. Your VPC. Your encryption keys. We deploy, hand over the keys, and step back. We're consultants, not landlords.

Integrations

Connects to everything you use

New tool in your stack? We plug it in. No rebuilding, no downtime. If your tool has an API, it works.

H
HubSpot
J
Jira
C
Confluence
S
Slack
O
Okta
G
GitHub
+ 40 more, and counting

Salesforce, Notion, Linear, Asana, Google Drive, SharePoint, Gmail, Outlook, Google Workspace, Azure AD, GitLab, ServiceNow — plus internal tools, legacy systems, and anything else with an API. We build the bridge.

The market is moving. Are you?

40%
of enterprise apps will run AI agents by year-end. Yours could be one of them — Gartner
23 min
gone every app switch — longer than the meeting they were prepping for — UC Irvine
FAQ

Everything you need to know

We deploy a custom AI agent directly into Slack — the tool your team already lives in. It connects to all your business tools — CRM, project management, documentation, email, code repos, and more. Your team asks questions in natural language, and the agent finds answers across every connected tool in one response. Unlike generic AI assistants, it respects your org's access controls, remembers context across conversations, and runs on your own infrastructure.

Built-in AI assistants (Slack AI, Teams Copilot) only search within their own ecosystem — they can't query your CRM or project tools. Microsoft Copilot is locked to Microsoft products. ChatGPT Enterprise doesn't connect to your internal tools or enforce granular RBAC.

Cleavis is built for Slack specifically — deep native integration, not a generic bot ported over. It connects to any tool via MCP, A2A (Agent2Agent), or a direct REST API — whichever protocol the target system actually supports — enforces per-user access control at the tool and data level, provides both short and long-term memory, and runs entirely on your infrastructure. You own everything.

Here's the thing most people miss: the AI agent doesn't have a master key to your data. Each person logs in as themselves — their own credentials, their own permissions. The agent can only see what that person is already allowed to see in each tool.

So when a sales rep asks a question, the agent queries HubSpot as that sales rep — not as some all-seeing admin account. Ask about payroll? The agent doesn't "deny access." It simply has no way to get there. The door doesn't exist for that user.

On top of that:

  • It runs on your servers — your AWS, your encryption, your rules. We deploy and leave.
  • EU regulation-ready — GDPR data access and deletion requests handled automatically with immutable audit trails. Same governance covers AI Act, NIS2, and DORA.
  • Every conversation is logged — not to spy on people, but so you have a clear answer when an auditor asks.
  • AI budgets per person — you set limits, the agent respects them. No surprise bills.
  • Admin controls live in the chat — natural language lets an administrator grant, revoke, or adjust access directly from the bot itself, no separate dashboard required for routine changes.

No tool changes needed. The agent connects to your existing tools via API — nothing to replace, nothing to migrate.

Day 1: Agent template deployed to your AWS. Day 2-3: Integrations connected. Day 3-5: Access control configured, pilot users testing. Week 2: Full rollout with 15-minute training.

Yes. We connect via whichever protocol fits — MCP (Model Context Protocol), A2A (Agent2Agent), or a direct REST integration. We're not locked into one standard, so any tool with an API can be connected. We build custom integrations for internal tools, legacy systems, and proprietary databases as part of the engagement.

Get Started
Free to start — no commitment, no pressure

Ready to unlock
your tools?

Tell us about your team and your biggest pain point. We'll reply with a tailored walkthrough — no sales pitch, no pressure, just a clear picture of how Cleavis fits your setup.

Live demo on your tools within a week
Pilot deployed in days, not months
A question costs a fraction of a cent. The app-switch it prevents costs 23 minutes.

Reach us directly: talk@cleavis.eu