Custom Ai ChatGPT Interface for Your Teams

If your team is already using ChatGPT (or any AI chat) at work, you’re probably seeing one of these two situations:

• Someone is paying with a personal card and expensing it.
• Nobody is paying, so people “just use whatever they have” — and you get zero visibility.

Sound familiar? This is exactly why we shipped our AI for Teams update: a private ChatGPT-style workspace for your organization, with procurement handled by us, and usage controlled by roles + token budgets.

The credit card problem (that nobody talks about)

Most organizations don’t issue credit cards to departments. Procurement exists for a reason.

But AI providers almost always expect a card on file. So the team ends up doing weird workarounds:

• Marketing lead subscribes with their own card.
• Ops team shares a single login (please don’t).
• Finance gets flooded with tiny reimbursements.

It’s not “a tooling issue”, it’s a procurement mismatch.

With Berlime, we procure the inference for you and deploy your own chat interface on your server. Your team gets access, procurement stays clean, and you don’t need to roll out corporate cards just so people can write better emails.

The underutilization problem (aka “why you feel AI is expensive”)

Most direct subscriptions are flat. Same plan, same price, whether the person uses it 5 times a day or 5 times a month.

That’s where costs quietly leak.

A simple scenario

Let’s say you have 20 users.

• Direct subscription: US$20/user/month → US$400/month
• Reality: maybe 8 people are heavy users, the other 12 barely touch it

You don’t have a good lever to pull. You either:

• cut access (and adoption dies), or
• keep paying for seats you don’t fully use

What we do differently

We don’t treat your company like one generic user.

We curate access by user groups and roles, then allocate tokens/credits per user so usage matches the job.

Example:

• Admin: short Q&A, rewriting, summarizing → small token budget
• Ops: SOP drafts, vendor emails, checklists → medium token budget
• Marketing: campaigns, long-form copy, research → larger token budget

That means you can roll AI out to everyone, without silently burning money on a one-size-fits-all plan.

Here are real prompts we see teams using (and why the budgets differ):

• Admin: “Rewrite this email to sound firm but polite.” / “Summarize this PDF into 5 bullets.”
• Ops: “Turn this SOP into a step-by-step checklist.” / “Draft a vendor reply with 3 options.”
• Marketing: “Give me 10 campaign angles for X, then write 3 ad variants each.” / “Research competitors and summarize positioning.”

The update: your private AI chat workspace

This is the same “ChatGPT-style” experience your team already understands — but built for organizations:

• No personal cards: we handle procurement
• Runs on your own server: your own infrastructure
• Custom domain: e.g. ai.yourcompany.com
• All major models: OpenAI, Google, and more (we pick the right mix for your workloads)
• Usage transparency: track adoption, cost per team, cap spend before surprises hit
• Quarterly check-ins: we review usage and optimize what you’re paying for
• Per-user token caps: each plan comes with a monthly allowance (and optional top-ups) so you can budget properly

A pricing example that actually matches real teams

Let’s take a small company with 15 users across 3 departments.

• 5 in marketing on Nexus (S$39/user/mth) → S$195/mth
• 5 in operations on Pulse (S$29/user/mth) → S$145/mth
• 5 in admin on Flare (S$19/user/mth) → S$95/mth

Total: S$435/month, and each group gets a plan that matches how they work.

Now compare that to a flat subscription approach. Even if the numbers are “close”, you still lose the most important controls:

• You can’t cap spend by role.
• You can’t stop overpaying for underused seats without killing access.
• You can’t standardize access under your domain + your deployment.

This is the difference between buying AI and operationalizing AI.

“So what do we need to get started?”

Here’s the straightforward part (no fluff):

• One-time build + deployment: S$2.5k (runs on your own server)
• Minimum: 10 users
• Timeline: typically up and running within 14 weeks (business hours)
• Contract: 2 years so we can learn your workflows and optimize adoption + spend (renewals yearly after)

If you want to start small, start with 10 users, set conservative token caps, and expand only when you see usage patterns.

The real win

AI in companies doesn’t fail because the model is weak.

It fails because:

• procurement is messy,
• access is inconsistent,
• and costs are untracked until someone asks “why did we spend so much?”

This update fixes that — with a private chat interface, curated token budgets, and procurement handled properly from day one.