Up to ~20% reduction* in LLM spend through a single line of code




“With Merge Agent Handler, we can bring a broader set of data connectors to our users faster and constantly expand what our customers can do with Perplexity Enterprise Pro.”




“Before launching our HRIS integrations, a few team members at Merge came on-site to train our customer-facing teams on marketing, selling and supporting the integrations. This took additional work off of my team’s plate and has helped us take the integrations to market more efficiently.”

“Working with Merge’s Unified API and beautiful React component took less than a sprint to integrate, test, and release.”

“Merge’s post-sales team is truly amazing. They’re fast, responsive, and deeply knowledgeable of HRIS integrations and our use case.”


Every portfolio company independently rebuilds AI infrastructure from scratch. The inefficiency compounds across the portfolio.
Engineering hardcodes one model across all use cases.
Provider invoices don’t break out spend by product, team, or customer. Can’t set limits until after costs spike.
Every portco spends months building the same cost controls from scratch. No shared leverage, no compounding value.

Your portco swaps one URL. Everything else stays the same, including code, SDKs, prompts, product.
Every request is routed to the lowest-cost model that meets quality requirements.
Reduce LLM spend from the first invoice. No engineering work. No rollout risk.
Same integration. Same playbook. No product changes required.
This is not a one-time optimization.
It’s a playbook you apply across every company.


A mid-market SaaS company spending $1M/year on LLM inference. Here’s what happens after a 1-minute integration.
Engineering hardcoded every AI call to the same model, paying premium rates for simple tasks that don't need them
Each task gets routed to the cheapest model that maintains quality.
| Task type | % of calls | Routing change | Cost /M tokens |
|---|---|---|---|
| Simple tasks (tagging, extraction) | 50% | GPT-5.5 → GPT-5.4 nano | $0.80/M |
| Mid-complexity (chat, summaries) | 30% | GPT-5.5 → Sonnet 4.7 | $0.30/M |
| Complex reasoning | 20% | GPT-5.5 → GPT-5.5 (no change) | $30/M |
No new headcount. No engineering project. Pure margin improvement from month one.
Merge charges LLM cost plus a small margin. No platform fees.
No per-seat charges. The margin shrinks as you scale.
Portcos | Merge margin | Est. annual savings | |
|---|---|---|---|
Portcos | 1–3 | 5.0% | $320k |
Growth | 4–7 | 4.7% | $893k |
Scale | 8-14 | 4.4% | $1.81M |
Portfolio | 15-24 | 4.2% | $3.24M |
Enterprise | 25+ | 4.0% | $4.2M+ |

Start with one portco. See results in the first month. Scale from there.
