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We partnered with Prime Intellect to build Fast Ask, a small RL-trained subagent that helps our Sheets agent find answers in spreadsheets. It scores +4% over Opus on exact match accuracy at Haiku latency.

We partnered with Prime Intellect to build Fast Ask, a small RL-trained subagent that helps our Sheets agent find answers in spreadsheets. It scores +4% over Opus on exact match accuracy at Haiku latency.

331,815 次观看

Your work is now saved in Ramp Sheets. Every sheet you build automatically backs up to the cloud. Open the menu to jump back into any past project instantly.

Your work is now saved in Ramp Sheets. Every sheet you build automatically backs up to the cloud. Open the menu to jump back into any past project instantly.

17,662 次观看

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AI spend is measured in tokens, model calls, and dollars. However, none of these fields describe the actual work being done. At Ramp, we built a semantic layer that attributes agent spend to objectives and outcomes. This allowed us to go from monitoring AI spend to understanding AI ROI. Here's how we built it 🧵

AI spend is measured in tokens, model calls, and dollars. However, none of these fields describe the actual work being done. At Ramp, we built a semantic layer that attributes agent spend to objectives and outcomes. This allowed us to go from monitoring AI spend to understanding AI ROI. Here's how we built it 🧵

42,031 次观看 • 4 天前

Today, we're launching Ramp Agent Cards. There's been no safe way for agents to spend money, until now. Ramp Agent Cards give agents the ability to spend, governed with real spend limits, merchant controls, and full visibility into every transaction.

Today, we're launching Ramp Agent Cards. There's been no safe way for agents to spend money, until now. Ramp Agent Cards give agents the ability to spend, governed with real spend limits, merchant controls, and full visibility into every transaction.

844,124 次观看 • 5 个月前

Today, we’re launching Ramp Sheets, the AI spreadsheet editor built to 10x finance teams, operators, and founders. Ramp Sheets plans, executes, and formats automatically. It’s already being used to model budgets, forecast revenue, and reconcile financial statements.

Today, we’re launching Ramp Sheets, the AI spreadsheet editor built to 10x finance teams, operators, and founders. Ramp Sheets plans, executes, and formats automatically. It’s already being used to model budgets, forecast revenue, and reconcile financial statements.

1,326,960 次观看 • 9 个月前

We’re open-sourcing PorTAL, our framework for shared task representations and cross model LoRA adaptation. It now spans from hybrid attention models to multimodal systems including Gemma 4 E2B, Mistral 7B & Thinking Machines' Inkling. Code: ramp-public/portallib Models: Hugging Face /RampPublic

We’re open-sourcing PorTAL, our framework for shared task representations and cross model LoRA adaptation. It now spans from hybrid attention models to multimodal systems including Gemma 4 E2B, Mistral 7B & Thinking Machines' Inkling. Code: ramp-public/portallib Models: Hugging Face /RampPublic

171,002 次观看 • 1 个月前

We tested NVIDIA NeMo Switchyard’s stage router for coding agents in Ramp SWE-Bench. Routed agents showed comparable performance to single-model controls while substantially reducing costs and runtime.

We tested NVIDIA NeMo Switchyard’s stage router for coding agents in Ramp SWE-Bench. Routed agents showed comparable performance to single-model controls while substantially reducing costs and runtime.

97,863 次观看 • 25 天前

Today, we're releasing Ramp CLI to let agents manage your company's finances. 50+ tools across cards, bills, expenses, travel, and approvals. Fewer tokens than MCP, and comes with pre-built skills like receipt compliance and agentic purchasing.

Today, we're releasing Ramp CLI to let agents manage your company's finances. 50+ tools across cards, bills, expenses, travel, and approvals. Fewer tokens than MCP, and comes with pre-built skills like receipt compliance and agentic purchasing.

603,343 次观看 • 5 个月前

Introducing PorTAL: Portable Task Adapters for LLMs. A novel recipe to cheaply port fine-tuning between models. It matches per task LoRA accuracy at half the cost, lowering the switching overhead of adapting tasks across LLMs. At Ramp, every new model release used to mean retraining our fine-tunes from scratch. PorTAL learns the task once, then efficiently refits it onto any new base model, even across model families.

Introducing PorTAL: Portable Task Adapters for LLMs. A novel recipe to cheaply port fine-tuning between models. It matches per task LoRA accuracy at half the cost, lowering the switching overhead of adapting tasks across LLMs. At Ramp, every new model release used to mean retraining our fine-tunes from scratch. PorTAL learns the task once, then efficiently refits it onto any new base model, even across model families.

172,368 次观看 • 2 个月前

Introducing Steer AI. We made an AI that can't stop thinking about any concept you choose, by steering a model's internal representations at inference time. Ask it anything, and watch it bend reality around that concept. Available for one week only.

Introducing Steer AI. We made an AI that can't stop thinking about any concept you choose, by steering a model's internal representations at inference time. Ask it anything, and watch it bend reality around that concept. Available for one week only.

348,570 次观看 • 5 个月前

Today we’re releasing Ramp SWE-Bench: a private, production-grounded coding benchmark created from real engineering problems we've faced at Ramp.

Today we’re releasing Ramp SWE-Bench: a private, production-grounded coding benchmark created from real engineering problems we've faced at Ramp.

189,176 次观看 • 2 个月前

Meta just acquired Manus AI. Ramp Sheets modeled it out: Estimated price: $4-6B based on AI M&A comps Fastest to $100M ARR in history (8 months) Benchmark likely 8-12x'd in under a year

Meta just acquired Manus AI. Ramp Sheets modeled it out: Estimated price: $4-6B based on AI M&A comps Fastest to $100M ARR in history (8 months) Benchmark likely 8-12x'd in under a year

528,139 次观看 • 8 个月前

We modeled the SpaceX / xAI merger. – xAI holders get 22% of combined entity – $49B revenue by 2028 – SpaceX currently trades at 50x revenue At that multiple, the combined entity is worth ~$1.1T at IPO and $2.5T by 2028.

We modeled the SpaceX / xAI merger. – xAI holders get 22% of combined entity – $49B revenue by 2028 – SpaceX currently trades at 50x revenue At that multiple, the combined entity is worth ~$1.1T at IPO and $2.5T by 2028.

275,730 次观看 • 7 个月前

xAI just raised $20B at ~$230B. Ramp Sheets thinks it's a good deal: $383/user vs OpenAI's $1,875/user (80% discount) 600M users who already open X daily Only need 8% converting to $20/mo Grok to justify valuation

xAI just raised $20B at ~$230B. Ramp Sheets thinks it's a good deal: $383/user vs OpenAI's $1,875/user (80% discount) 600M users who already open X daily Only need 8% converting to $20/mo Grok to justify valuation

249,154 次观看 • 8 个月前

We built Anthropic's internal revenue model based on the latest reports. $4.5B → $148B in 5 years $100B in training costs Profitable two years before OpenAI

We built Anthropic's internal revenue model based on the latest reports. $4.5B → $148B in 5 years $100B in training costs Profitable two years before OpenAI

147,905 次观看 • 7 个月前

We deployed 10,000 background agents to security-scan our codebase. The system is simple, scales with compute, and runs on publicly available models. From the scan, we fixed several high-severity vulnerabilities.

We deployed 10,000 background agents to security-scan our codebase. The system is simple, scales with compute, and runs on publicly available models. From the scan, we fixed several high-severity vulnerabilities.

74,602 次观看 • 3 个月前

A finance team just sent us this. They ran a full budget vs. actuals analysis in under 5 minutes. Uploaded their budget P&L and 10 months of GL actuals. Ramp Sheets matched every line item, calculated variances, and flagged problem areas. This used to take half a day.

A finance team just sent us this. They ran a full budget vs. actuals analysis in under 5 minutes. Uploaded their budget P&L and 10 months of GL actuals. Ramp Sheets matched every line item, calculated variances, and flagged problem areas. This used to take half a day.

141,737 次观看 • 7 个月前

B2B SaaS switching costs collapse during competitor acquisitions. – 15% of their customer base enters consideration – CAC drops 3-5x – Conversion spikes 5-10x Capture a few % = years of compounding LTV. Plug in your competitor's customer count and see the opportunity ↓

B2B SaaS switching costs collapse during competitor acquisitions. – 15% of their customer base enters consideration – CAC drops 3-5x – Conversion spikes 5-10x Capture a few % = years of compounding LTV. Plug in your competitor's customer count and see the opportunity ↓

138,780 次观看 • 7 个月前

Anthropic just raised $30B at a $380B valuation. – $0 to $14B in revenue in under 3 years – 95x return for Series A investors – If they IPO at $1T, new investors 3x their money View the full investment analysis and path to $1T below.

Anthropic just raised $30B at a $380B valuation. – $0 to $14B in revenue in under 3 years – 95x return for Series A investors – If they IPO at $1T, new investors 3x their money View the full investment analysis and path to $1T below.

112,219 次观看 • 6 个月前

You can now upload files to Ramp Sheets. Watch the agent ingest a pitch deck, research competitors on the web, and reverse-engineer a full Operating Model & Valuation from a single PDF.

You can now upload files to Ramp Sheets. Watch the agent ingest a pitch deck, research competitors on the web, and reverse-engineer a full Operating Model & Valuation from a single PDF.

110,119 次观看 • 8 个月前

Grok 4.5 launched today. It displays frontier-level shell discipline, chaining Bash commands and filtering their outputs more frequently than any other model tested.

Grok 4.5 launched today. It displays frontier-level shell discipline, chaining Bash commands and filtering their outputs more frequently than any other model tested.

28,288 次观看 • 1 个月前

At Ramp, we've seen AI token spend skyrocket 13x among our customers since last January. We ran experiments where coding agents managed their own token budgets. They ignored them completely, so we employed a separate controller model to approve spend on their behalf.

At Ramp, we've seen AI token spend skyrocket 13x among our customers since last January. We ran experiments where coding agents managed their own token budgets. They ignored them completely, so we employed a separate controller model to approve spend on their behalf.

37,115 次观看 • 4 个月前