Admin UI

Run your firm's AI from one web page.

The admin panel that ships with AI In Your Pocket. Add or remove team members, switch AI models, attach client folders the bot can read — all from http://localhost:5680 on the office machine. No terminal. No reinstall. No restart needed.

See pricing →Setup guide

Why the admin UI matters to your IT.

Most private-AI tools assume the IT person who installs them is the same person who lives in a terminal. That's rarely true in a 5-50 person firm. Office managers, partners, and fractional IT need a web page, not a command prompt.

The admin UI is built around that. Everything that changes over time — who's on the team, which client folders the AI can see, which model it's using — lives on a single web page on the office machine. Bookmark it, get on with the day.

Localhost-bound (127.0.0.1:5680) — never exposed to your LAN, never reachable from outside the office. The security boundary is “can you sit at the machine?” — if you can, you're already trusted.

What each panel does.

Panel 1

Allowlist — your team

Paste Telegram numeric IDs from a spreadsheet column (one per line, comma-separated, semicolons — anything sensible). Optional shared label like "Sales team" or "Partner" applies to every new user in one go.

Remove a leaver with one click. The bot stops replying to them within ~1 second — no restart, no re-config.

Panel 2

Per-user memory — see who's been chatting

Every team member has their own private memory file. The panel shows turn count, file size, and last-active timestamp per user — so the admin can spot stale users, oversize histories, or wipe a colleague's memory on their request (GDPR right-to-erasure).

Panel 3

Ollama models — pull, swap, delete

If you're using local Ollama as your AI engine (the privacy-first default), this panel lists every model installed on the machine. Pull a new one by typing its tag — progress bar appears in real time. Swap which model is active with one click; the bot picks it up on the next reply (no restart).

Honest experimentation: start with llama3.2:3b on a modest machine, pull qwen2.5:14b when you upgrade hardware, drop the smaller one when it's not earning its disk space.

Panel 4

Shared client folders — your AI knows your projects

Attach a folder on your office machine (or a mapped network drive) and the bot can read its files when your team asks. Read-only — the AI can never modify, move, or delete anything. Files stay on your machine; the AI just gets to see them.

Add a folder by typing an alias ("Acme matters", "FY25 audits") and the path. Behind the scenes a host-side helper service creates a Windows junction inside a mounted parent dir; the folder is searchable + readable from Telegram within ~5 seconds.

When a project finishes or a matter closes, remove the folder with one click. The files themselves are untouched on disk — only the junction unlinks.

Team member asks:
Where are we with Mr Khan selling the house on Maple Avenue?
Bot replies (citing files):
Looking at your 'Acme matters' folder. The Maple Avenue conveyance for Mr Khan is at exchange — contract dated 14 Apr, deposit cleared 17 Apr. Latest from the chain (chain.md) shows the buyer's solicitor is waiting on a search response, target completion 6 May. Outstanding action on your side: confirm completion funds with the lender. (Cited: matters/Khan-Maple-Ave/chain.md, matters/Khan-Maple-Ave/exchange-letter.pdf)
Panel 5

Indexer — search across all attached folders

The indexer turns every text file across every attached folder into searchable chunks the bot can retrieve. When your team asks a broad question, relevant snippets from across all folders are prepended to the AI's context with file-path citations.

Force a re-walk with one button when you've added a lot of new files. Re-index time is roughly 5 minutes per 1,000 small files (one-off; subsequent walks only re-embed changed files).

What “folders make the AI useful” actually looks like.

Attach the right folders and the AI stops being a generic chatbot. It becomes the colleague who already read every file. Some real examples, by sector:

Law firm — conveyance

“What stage is the Smith sale?”

Folder attached: D:\Matters\Conveyancing. Bot retrieves from Smith-Riverside-Drive subfolder, finds the latest exchange + completion notes, replies with current chain status, outstanding actions, and the next deadline — with file-path citations the fee-earner can click in Explorer.

Accountancy — client review

“Quick summary of Acme's Q3 management accounts?”

Folder attached: D:\Clients\Acme. Bot retrieves the Q3 management-accounts.xlsx commentary, the bank reconciliation notes, the email thread about an unusual transaction — produces a partner-ready summary citing each source file. Trainee saves an hour of skim-reading before the meeting.

Property management

“What's the status of the Section 20 at Riverside Court?”

Folder attached: D:\Blocks\Riverside-Court. Bot finds the latest S20 stage (consultation notice issued 12 Mar, observation period closes 18 Apr), summarises leaseholder objections received, lists the contractor estimates being compared. Property manager opens the cited PDFs in one click.

Recruitment

“Who have we submitted for the Acme infrastructure role?”

Folder attached: D:\Roles\Acme-Infrastructure-Engineer. Bot lists candidates in the candidate-submissions.md file with submission date, current stage, last note from the consultant. Saves the recruiter from opening 20 individual CV folders.

Architecture — live project

“Where are we with the Building Regs response on the Mill?”

Folder attached: D:\Projects\Mill-Conversion. Bot retrieves the BCO correspondence, the structural engineer's report, the planning officer's questions — replies with what's outstanding and what's been answered, citing each document. Architect prepares the response email with one paste.

In every case the folder content stays on your machine. The bot reads chunks at query time and (with local Ollama) does the reasoning entirely on your machine too — nothing leaves your office.

Why this changes how your IT person feels about it.

Most “private AI” tools punish the IT person who installed them. Every change — new joiner, new project folder, model upgrade — means SSH, a YAML file, a `docker compose down`, and a restart that sometimes wipes state.

This is the opposite of that. After install, the IT person never needs to touch a terminal again to do anything operational. Web form, click, done. The product gets out of their way and stays out.

That's why managers buy this for IT teams who've already pushed back on three other AI tools. The setup is honest about being technical; everything after install is honestly easy.

Ready to run your firm's AI from a web page?

See pricing →How install worksBy sector