Compresr
LLM context compression for better accuracy and cost reduction
Website: https://compresr.ai/
Cover Block
| Field | Value |
|---|---|
| Name | Compresr |
| Tagline | LLM context compression for better accuracy and cost reduction |
| Headquarters | San Francisco |
| Founded | 2026 |
| Stage | Seed |
| Business Model | API / Developer Platform |
| Industry | AI Infrastructure |
| Technology Type | AI / Machine Learning |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (4) |
| Funding Label | Seed (Y Combinator W26) |
Links
- Website: https://compresr.ai/
- Y Combinator profile: https://www.ycombinator.com/companies/compresr
- GitHub: https://github.com/Compresr-ai/Context-Gateway
- LinkedIn (Ivan Zakazov, co-founder): https://www.linkedin.com/in/ivan-zakazov/
- LinkedIn (Berke Argın, co-founder): https://www.linkedin.com/in/arginberke/
- LinkedIn (Oussama Gabouj, co-founder): https://ch.linkedin.com/in/oussama-gabouj-775235194
Summary and Signal
Compresr is a Y Combinator W26 company building an API that compresses the context fed into large language models so that downstream agents and retrieval-augmented generation (RAG) workflows run cheaper and more accurately [Y Combinator, 2026]. The startup was founded in 2026 by Berke Argın, Kamel Charaf, Oussama Gabouj, and Ivan Zakazov, and reports four employees [Y Combinator, 2026]. Its product is positioned as a drop-in proxy for agent and RAG pipelines, framed by the founders as a defense against "context rot" [LinkedIn, 2026]. The team has shipped an open-source component called Context Gateway, described on GitHub as "an agentic proxy that enhances any AI agent workflow with instant history compaction and context optimization" [GitHub, 2026]. Compresr was named among Forbes' selection of promising W26 startups [Forbes, 2026].
Data Accuracy: GREEN -- Confirmed by Y Combinator, GitHub, Forbes, and founder LinkedIn profiles.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Seed (YC W26) |
| Business Model | API / Developer Platform |
| Industry / Vertical | AI Infrastructure |
| Technology Type | AI / Machine Learning (prompt and context compression) |
| Geography | San Francisco, USA |
| Growth Profile | Venture Scale |
| Founding Team | 4 co-founders |
| Funding | Seed, amount undisclosed, Y Combinator |
Company Overview
Compresr was founded in 2026 by Berke Argın, Kamel Charaf, Oussama Gabouj, and Ivan Zakazov, and is part of Y Combinator's Winter 2026 batch [Y Combinator, 2026]. The company is headquartered in San Francisco [Forbes, 2026]. The legal entity is referenced on LinkedIn as "Compresr Inc." [LinkedIn, 2026]. The team's stated mission is "fighting context rot," the operational problem that LLM responses degrade as the context window fills with stale or low-signal tokens [LinkedIn, 2026].
Key milestones to date include incorporation, admission to Y Combinator W26, publication of the Context Gateway repository, and selection by Forbes as one of 21 "most promising" W26 startups [Forbes, 2026].
Data Accuracy: GREEN -- Confirmed by Y Combinator, Forbes, and the company's own GitHub and LinkedIn surfaces.
The Product and the Stack
Compresr's commercial product is an API that compresses LLM context, positioned as a drop-in for agents and RAG pipelines to cut token costs and improve accuracy [Y Combinator, 2026]. The company's marketing site frames the offering as "context compression technology" [compresr.ai]. The public technical artifact is the Context-Gateway repository, described as "an agentic proxy that enhances any AI agent workflow with instant history compaction and context optimization tools" [GitHub, 2026]. A 2026 arXiv preprint titled "Cmprsr: Abstractive Token-Level Question-Agnostic Prompt Compressor" shares the company's name [arXiv, 2026].
Data Accuracy: YELLOW -- Product framing is corroborated by YC, GitHub, and the company site; performance claims are vendor-side and not yet independently benchmarked in the cited research.
Market Research and Opportunity
Compresr targets the inference-cost layer of generative AI. The YC Tier List entry frames LLM inference cost reduction as a massive pain point for companies building on foundation models [YC Tier List, 2026]. Demand drivers include agent workloads, which accumulate history, and RAG pipelines, which retrieve documents [GitHub, 2026] [YC Tier List, 2026]. Founder commentary on "context rot" positions compression as a Pareto improvement for both cost and accuracy [LinkedIn, 2026].
| Metric | Value |
|---|---|
| Reported latency improvement in founder demo | ~30% faster with proxy |
| Third-party blog claim on agent cost reduction | up to 76% |
| Compresr employee count | 4 |
Data Accuracy: YELLOW -- Demand framing is corroborated by YC and founder commentary; quantified market sizing is not present in the captured sources.
The Competitive Field
Compresr enters a niche where the most credible incumbent is a Microsoft Research project.
| Company | Positioning | Stage / Funding | Notable Differentiator |
|---|---|---|---|
| Compresr | API and proxy for LLM context compression | Seed, YC W26 | Drop-in agentic proxy (Context Gateway) |
| LLMLingua (Microsoft) | Research-led prompt compression library | Microsoft Research | Published benchmarks, broad academic citation |
Opportunity
Compresr aims to become the default optimization layer between production AI agents and foundation models. The proxy form factor lowers the integration tax, and the "context rot" framing converts the pitch into a product-quality argument [LinkedIn, 2026].
Data Accuracy: YELLOW -- Scenarios are analyst constructions grounded in cited positioning and YC distribution evidence; no revenue, customer, or valuation figures are publicly disclosed.
Sources
- [compresr.ai] compresr - Context Compression | https://compresr.ai/
- [Y Combinator, 2026] Compresr: LLM context compression for better accuracy | https://www.ycombinator.com/companies/compresr
- [YC Tier List, 2026] Compresr - YC Tier List | https://yctierlist.com/w26/compresr/
- [GitHub, 2026] Compresr-ai/Context-Gateway repository | https://github.com/Compresr-ai/Context-Gateway
- [LinkedIn, 2026] Ivan Zakazov - fighting context rot @ compresr.ai (YC W26) | https://www.linkedin.com/in/ivan-zakazov/
- [LinkedIn, 2026] Oussama Gabouj - Cofounder and CTO @ Compresr Inc. | https://ch.linkedin.com/in/oussama-gabouj-775235194
- [LinkedIn, 2026] Berke Argın - Compresr (YC W26) | https://www.linkedin.com/in/arginberke/
- [Forbes, 2026] Meet The New Y-Combinator Startups Poised To Change Tech | https://www.forbes.com/sites/dariashunina/2026/03/16/21-most-promising-startups-from-y-combinators-latest-batch/
- [Menlo Times, 2026] Y Combinator Launches of the Week | https://www.menlotimes.com/post/y-combinator-launches-of-the-week-72
- [arXiv, 2026] Cmprsr: Abstractive Token-Level Question-Agnostic Prompt Compressor (2511.12281) | https://arxiv.org/abs/2511.12281
- [emelia.io, 2026] Context Gateway: Cut Your AI Agent Costs by 76% | https://emelia.io/hub/context-gateway-ai-agent-cost-reduction
Articles about Compresr
- Compresr Wants Every AI Agent's Prompt to Travel Half as Light — The Y Combinator W26 startup is selling an API that squeezes LLM context windows for agents and RAG pipelines burning tokens at scale.