Determa Determa Applied AI Systems

One context layer.
Every role.

The context layer joins your chat, tickets, wiki, CRM and meetings into one model of the business, and hands every role the context it needs, with the source. Here is what that looks like at their desks.

↓Scroll through 8 worlds

Managing directors know by 8:00 what changed.

One short brief at the start of the day: what moved with your customers across chat, tickets, wiki, CRM and meetings, every line with its source. Someone who was not in the meeting learns what was decided without asking anyone who was.

Account managers catch every customer change.

What changed since you last looked, folded per customer, the mention cited or the item dropped. 1 day at minimum, 7 at most, so a week away is caught up instead of silently lost. A source that did not answer is named, so a quiet radar and a failed read never look the same.

Project leads leave the call with decisions, not notes.

The meeting is written up while it runs: notes, decisions, who agreed to do what. Each decision lands in your proposals, one row at a time, to accept, edit or decline. Colleagues get the write-up, never the transcript.

Sales sees the deal next to the work.

CRM stage and close date right beside the ticket that holds up the go-live. The question no single system answers, answered in one place, with both sources.

New colleagues ask the company and get sources.

Ask about a customer, a page, a decision. The answer cites where it comes from, shows only what you may see, and says “not found” instead of inventing one.

Team leads let AI act and still sign every action.

Comment on the ticket, append to the wiki page, reply in the thread, create a work item, all as yourself. Nothing is written until you tap approve. Every tap leaves a receipt, and a decline is an audited decision too.

IT leads keep it in their own tenant.

It runs in your company’s cloud tenant, with model processing locations verified for each deployment. Answers are trimmed per person, no external action runs without authorization, and every step is audited. Production-ready before anyone says yes.

Engineers plug the same context into Claude and Codex.

The same backend over MCP, inside Claude, Codex and any MCP-enabled app. Same identity, same approval gate, same audit trail as in chat. Nothing new to govern.

Chat
Tickets
Meetings
Wiki
CRM
brief ready4 changes
Helio GmbH4 since Friday4
Tessin LogistikCRM2
Lindner Bauquiet0
Away
3 days away
MKCan the import go in before go-live?
HK1,200 legacy items.
SBThen week 41.
Proposals
CRMHelio GmbH
Review · close 31 Oct
Ticket 218Bulk import
Statusblockedin progress
Helio GmbH
AFnew on the teamday 3
?Meeting3 Sep · Helio weekly
?Ticket218 · bulk import
not foundno source, no answer
APPROVED

RECEIPT r-2291

comment · ticket 218

as M. Keller · 09:42

audited ✓

your tenant · EU
EUverified
Claude Desktopconnected
Claude Codeconnected
Codexconnected
Coworkconnected
any MCP appconnected
context layer
CHAT · TICKETS · WIKI · CRM · MEETINGS
context layer · morning brief · Tue 07:58
Good morning. 4 changes since yesterday.
  • Helio GmbHgo-live moves to week 41meeting · said by the client
  • Tessin Logistikcontract review, close 31 OctCRM
  • Ticket 218waits for the go-live windowTicket · S. Brandt
  • Wikidid not answerretry 08:15
Every line sourced. Nothing invented.
context layer · radar
HelioTessin
Since you last looked · 3 days
Helio GmbH4go-live week 41 · meetingbulk import requested · chat
Tessin Logistik2contract review · CRM
Lindner Bau0quiet · every source read
wiki did not answer · named
context layer · meeting · Helio weekly
liveHelio weekly

MKCan the bulk import go in before go-live?

HKWe have 1,200 legacy items.

SBThen go-live in week 41, not 40.

MKSpec comes by Friday.

Proposals · 3
decision · said by the clientGo-live in week 41
AcceptEditDecline✓ accepted
commitment · M. KellerImport spec by Friday
decisionSandbox stays deprioritised
context layer · Helio GmbH · deal and work
CRM
Helio GmbH
LeadOfferReviewWon
Close31 Oct
Depends ongo-live windowon track
Tickets
Helio go-live
#218 bulk importblockedin progress
PR #512 import pathmerged
go-live windowweek 41
close on track · both sources
context layer · ask the company
What did we decide on the Helio bulk import?
The import goes in before go-live, up to 1,200 items. Go-live is week 41.
meeting 3 SepTicket 218
What penalty is in the Tessin contract?
Not found in the sources you may see.
Ask the company …
context layer · review
Review·pendingapproved 09:42·asked once · no duplicate
Helio GmbH · feature request · bulk import
Source: chat #helio-delivery, M. Keller, today 09:40
Helio asked whether the import can take 1,200 legacy items before go-live.
Proposed: comment on ticket 218 as you, verbatim.
ApproveEdit wordingDecline
Nothing is written until you tap.
context layer · tenant · audit log
ChatTicketsWikiCRMMeetings
→
your cloud tenantEU
knowledge graph
inference · EU
approval gate
read · chat #helio-delivery · as M. Keller
proposal staged · review r-2291
approved · M. Keller
written · ticket 218 · receipt
0 external actions without authorizationanswers trimmed per person
Claude · MCP · context layer

›Where do we stand with Helio?

⏺ context.search("Helio")

⎿ 3 facts · meeting 3 Sep · ticket 218 · CRM

›Comment that on ticket 218.

⏺ context.propose(ticket: 218)

⎿ pending · same gate as in chat

✓ approved by M. Keller · receipt r-2292

And plenty more roles.

Wherever someone needs to know what was said, decided or changed, and act on it with a person in charge.

Data protection

Every shared fact carries a recorded consent. Nothing becomes company knowledge until a person confirms it.

Back from holiday

7 days of changes, folded per customer, instead of a wall of unread messages.

Chiefs of staff

The brief before the meeting: what is open with this customer, and who said it.

Customer support

Ticket, chat mention and last call about one customer in one answer. The reply goes out as you, after approval.

Auditors

Every approval, every decline, every receipt, traceable to a person and a time.

Delivery managers

Blocked tickets next to the date promised to the customer, before the customer asks.

Every world. One context layer.

The roles change. The model of the business underneath stays the same: sourced, permissioned, approved.

Scenes are synthetic: real surfaces, fictional customers, people and records.

WHAT A TEMPORAL KNOWLEDGE GRAPH SHOWS

Which commitment applies when?

One launch, two dated commitmentsFictional example on 1 October. Customer A has a launch. The agreed launch was 12 October from 09:00 until 11:30, sourced from CRM. A reviewed customer call explicitly changes it to 19 October, effective 11:30. Both facts and their sources remain in the graph.hasCustomer ALaunchagreed date09:00–11:3012 OctSource: CRMFrom 11:3019 OctSource: reviewed call
As of 1 Oct

As of 11:30: launch on 19 October.

The agreed change takes effect at 11:30. The earlier commitment and both sources stay traceable.

Fictional example · reviewed customer call

The Context Layer in action

Sanitized reconstruction of the operational workflow with fictional records. It shows Pulse, the Action Inbox, Proposals, record mapping and governed sharing; no client system or data appears. Narrated with René Zander’s cloned voice. Discuss a project →

Founded and led by René Zander · Enterprise AI Architect · 19 years of enterprise IT

Why René Zander stands behind it

René Zander, founder of Determa
René Zander
Enterprise AI Architect

You hire Determa. The work is delivered by the person who designed the system.

Determa grew out of 19 years of enterprise IT — out of projects where systems had to do more than work: they had to survive operation, pass review, and be handed over. René Zander leads every Determa engagement personally: architecture, guardrails, handover. No sales team promising something a delivery team has to keep later.

References, case studies and a full sample scope for production operation remain on renezander.com. Determa delivers the engagements.

René Zander leads Determa and takes responsibility for architecture, implementation and handover.

Next step

Let us check whether your AI initiative is production-ready.

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