Connecting an LLM to your stack is easy. Making it work company-wide isn’t.
Many teams start by wiring an LLM or their procurement tool’s AI connector to their spend systems. Here’s what it takes to make it work reliably for every employee, and when building it yourself makes sense.
An LLM wired to your systems with a connector. It demos well.
- One data layer across ERP, P2P, contracts, email, and org chart
- Permissions for the whole company, audited
- Evaluation sets, re-run on every change
- Model routing and token cost controls
- Proactive insights, alerts, and actions
- Support within a day
- Rollout and adoption, company-wide
Not a chatbot on your ERP. Answers, alerts, and actions.
The self-service layer for everyone who owns vendors and budgets, in Slack and Microsoft Teams.
PO-2231 Venue (Austin): $18,000 left · PO-2240 AV vendor: $15,700 left · PO-2256 Catering: $7,500 left
Illustrative example. Answers, alerts, and actions in Slack or Microsoft Teams.
Every spend question, answered
“How much is left on my POs?” “Has this vendor been paid?” “When does this contract renew?” Live from your ERP, procurement, contract, and email systems, with the source record behind every answer.
Fires caught before they start
An out-of-budget PO, a late invoice, a stuck approval, a late payment, a renewal coming up, a contract with no owner. The right owner hears about it first.
Fixed where people work
Submit a purchase request, file a change order, close a PO, all through your existing approval rules.
Three ways to get there. What each leaves to your team.
DIY: Claude / ChatGPT / Copilot + connectors
Prototyping and power users who know the data.
Joining systems, permissions, accuracy, cost control, upkeep.
Your procurement tool’s AI assistant
Procurement users working inside that tool.
ERP, contracts, AP system, org chart, email, and your policies and procedures; budget owners outside procurement; cross-system automations.
Partner Element
Every budget owner, across every spend system, in Slack or Teams.
Your approval rules. The rest is ours: data layer, permissions, evals, upkeep, support.
The build is only the first cost.
Connecting the model is the easy part. The real comparison is the cost of owning the system after launch.
| Build it yourself | Partner Element | |
|---|---|---|
| Total cost to own | Launch is the start. API changes, new fields, policies, models, and user issues become an internal product backlog someone has to own. | One product and team owns the spend layer: integrations, permissions, evaluations, model routing, upkeep, and support. |
| Answers across systems | Have a data lake (Snowflake, Databricks)?The joins may exist, but you still need employee-level permissions and write-back into source systems. No data lake?You also need to join records across ERP, P2P, contracts, AP, and email. | An AI-ready spend data layer that already links POs, invoices, payments, contracts, and approvals across your stack. |
| Company-wide permissions | A data lake solves the join, not who should see what. You map access and keep it current as people and teams change. | Permissions across systems by role, cost center, team, vendor, and contract ownership. Every change is auditable. |
| Accuracy | Every new question, field, policy, integration, or model change can change the answer. Someone has to define expected results and retest. | Automated accuracy checks every day. New models are tested against our evaluation sets before rollout. |
| Proactive insights | You decide what matters, who should hear about it, and when, then build each workflow. | PO attention digests and stuck-request alerts go to the right owners automatically. |
| Actions | Every write-back needs its own permissions, approval logic, error handling, and audit trail. | Requests, change orders, and PO close-outs run through your existing approval rules. |
| AI cost | Quotas make spend predictable by stopping work at the limit. You still own the tradeoff between cost, answer quality, and availability. | We optimize routing and computation behind the scenes. Our weekly PO digest fell from $9 to under $0.05 per recipient. |
| Gets smarter | Learns only from your own team’s mistakes, one bug report at a time. | Learns from edge cases and evaluations across all our customers. Patterns are shared, never your data. |
| Rollout | A working prototype still needs onboarding, feedback, issue handling, and trust before the whole company relies on it. | Built for employees in Slack or Teams. Flagged answers get a human follow-up within 24 hours. |
Compare ongoing ownership, not just development to launch.
When you should build it yourself
Is your spend process genuinely unique, with no product that fits?
Yes → building may be justified.Do you have a dedicated AI + finance-systems team and multi-year funding?
Run it as a product, not a side project.Do only a few finance power users need answers, mostly from one system?
Yes → an LLM plus a connector may be enough.Otherwise, buy.
If employees across the company need exact, permissioned answers across systems, and you want issues caught before they become fires.
Built to pass your IT and security review.
Not a new system of record
Partner Element works across your existing ERP, procurement, contract, AP, email, and company data.
Your approvals stay in charge
Actions follow your existing approval rules, rather than creating a parallel process.
Permissioned by employee
Access follows cost center, team, vendor, and contract ownership, not one shared service account.
Traceable answers and actions
Answers link back to source records. Changes and actions are logged for review.
Enterprise security
Built for sensitive company data: SOC 2, SSO, and customer data is not used to train AI models.
Questions we hear
Our procurement tool already has an AI assistant or MCP connector. Isn’t that enough?
It’s great for procurement users working inside that tool. Partner Element answers across procurement, ERP, contracts, and email for every budget owner, alerts them before issues, and lets them act in Slack or Teams, with one set of permissions.
We already have Glean, Slackbot, or Copilot.
Keep them. Horizontal assistants are built to search documents. Spend questions need exact joins across transactional systems, spend-specific permissions, and write-back actions. Partner Element handles that layer.
What happens when an answer is wrong?
Anyone can flag it in Slack or Teams. We follow up within 24 hours, fix it, and add the case to our daily checks so it stays fixed.
How fast can we prove it?
Live within a week on the integrations you already have. We’ll run your team’s 50 most common spend questions and measure accuracy, questions taken off finance’s plate, and time to answer.
Book your personalized demo
We’ll tailor it to your spend stack and biggest headaches.
Contact us: support@partnerelement.com