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Put years of work behind your next question.

From what happened this morning to why a decision was made three years ago, Hartlib brings the history of an entire company into one conversation.

How much are we paying our payroll provider this year?
Compiled in2.4s11 sourcesSAP, Gmail, Google Drive, Slack, Confluence+6

€38,400 this year. We signed two years ago at €31,200. Most of the increase comes from headcount growth and a compliance add-on added last March.

Why did we switch providers?

We switched after three payroll corrections in two months and repeated delays in tax filings with the previous provider.

Finance recommended the move after the second quarterly review, and the new contract started the following January.

Did the switch fix the problems?

Mostly. Tax filings have been on time since the switch, and payroll corrections dropped sharply.

Contractor adjustments are still a recurring issue. Finance raised them in the last two quarterly reviews, and the issue remains open.

Ask what no single system can answer.

A useful answer may depend on what happened across teams, tools, people, and time. Hartlib brings that history together before answering.

Which rollout plan is approved for the October launch? The September 4 plan is still the approved version, with launch scheduled for October 22. A September 6 draft proposes October 15 after the customer asked for an earlier date, but I found no approval for that change. The latest Operations review still references October 22, so that is the date to work from.

The work you've already done should keep paying off.

Keep people focused

Move forward without tracking down who remembers, interrupting their work, or scheduling a catch-up just to piece together what already happened.

Reach decisions faster

Start with the relevant facts already in view, so less time goes into searching, checking, and rebuilding context before deciding what to do.

Build on experience

Reuse earlier decisions, attempts, outcomes, and lessons instead of rediscovering them, so each new problem starts further ahead than the last.

04 · Current state

See what changed. Know what still holds.

Plans move, approvals change, and later requests do not always replace what was already agreed. Hartlib follows the history to show what applies now.

Why was the app launch moved to October, who approved it, and what still needs to be done?
New launch date: October 14, 2026
1 open risk
Originally planned for September 22

  1. Pending payment approval delayed launch

    Merchant account was still under review.

  2. Launch date change proposed

    Klara Vogel, Head of Product.

  3. Launch date change approved

    Felix Brandt, CEO.

  4. Payments unblocked

    Merchant account approved.

  5. At risk

    Redirect task still unassigned

    Old URLs still need redirects.

Illustrative example · Synthetic records

05 · Experience

Don't solve the same problem twice.

Bring earlier attempts, decisions, and outcomes into the problem in front of you. Hartlib shows what helped before, what failed, and what is different this time.

Have we run into this launch delay before?
Compiled in1.8s8 sourcesSlack+7

Yes. Two earlier launches slipped after final assets arrived too late. Moving asset approval one week earlier prevented the same issue on the following releases.

This time, the assets are already approved. Translation review is the remaining blocker.

06 · Evidence

See why the answer is true.

Every conclusion stays connected to the records behind it. Open the source, check the evidence, and see where the answer is confirmed, inferred, conflicting, or still unresolved.

Two sources disagree. The approved quote in Google Drive says 15%. In a later Google Meet call, Julia told Northstar that 20% had been approved. No revised quote or approval record resolves which discount actually applies.
Illustrative example · Synthetic records

Know what was promised and when

Commitments stay linked to who made them, when, and the context around them, so important follow-ups do not get lost between conversations and tools.

Take over without starting over.

Step into ongoing work with the decisions already made, the issues still open, and the commitments that still need to be kept.

Start with the history you already have.

Connect the tools your team already uses and bring their existing history into Hartlib. Conversations, documents, projects, and decisions can become usable memory from the start, not just from the day you connect it.

Memory growth

326.8k52.7%

Last 30 days

Connected data sources and their current states
AuthenticationActions
Slack
Ready
OAuthConnected
14.6k2 min ago
Google Drive
Syncing78%
OAuthConnected
38.4kNow
Jira
Ready
API tokenExpires in 24 days
12.1k4 min ago
ChatGPT
Ready
Compliance APIExpires in 18 days
6.7k3 min ago
GitHub
Ready
GitHub AppConnected
31.6k11 min ago
Salesforce
Paused
OAuthReconnect required
8.2k6h ago
Microsoft Teams
Ready
OAuthConnected
21.2kNow
Notion
Ready
OAuthConnected
18.9k2 min ago
Dropbox
Ready
OAuthConnected
9.4k4 min ago
99.98%

lower cost to process data

48×

faster to ingest data

A different kind of scalable AI memory, built on deterministic language compilation instead of per-record LLM extraction.

The whole company doesn’t mean everyone sees everything.

Hartlib can draw on shared history without flattening the access boundaries around it. Each answer reflects only the information the person asking is allowed to use.

Where does the October launch stand, and how much budget do we have left?

The launch is scheduled for October 14. Assets are approved, and translation review is still open.

You don’t have permission to view the budget information, so I can’t include it in this answer.

Request access to budget information?

Ask for permission to use this information in your answers. Access needs to be approved first.

Illustrative permissions example · Synthetic records

Memory everywhere it’s needed. Data only where you allow it.

SaaS

Start in minutes.

Sign up, connect your tools, and invite your team. We manage the infrastructure, models, scaling, and updates for you.

Self-hosted

Inside your environment.

Run Fortiana in your private cloud, VPC, or data center. Your data and models stay inside your infrastructure, fully under your control.

Air-gapped

Built for full isolation.

Fortiana runs fully offline, with no internet connection. Local models and dedicated hardware let it run in a fully disconnected environment.

Use Fortiana in the cloud or run it on your own infrastructure. No matter where it runs, memory stays under your control.

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