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Introducing Merge’s Universal Context Layer.
It substantially decreases token cost while increasing accuracy.
Every company uses AI wrong:
Say your designer makes a deck using Claude. They teach Claude your design systems and typography.
Now a Marketing hire makes a deck. None of the information your designer taught Claude gets passed over… why?
Merge fixes this:
All knowledge and memory across your entire company gets stored inside our context layer.
When someone on the org teaches Al, that skill lives across the entire organization instead of staying locked in their session.
Your AI runs faster, cheaper, and with more accuracy. You don’t have to switch systems, incur more costs, or retrain anyone on your team, Merge runs invisibly in the background.
Book a demo here: merge.dev/merge-for-workforc…
Testing out the new @merge_api SF office before we move in officially next week!
✨️
Shensi Ding retweeted
Shensi Ding retweeted
Dots from @OpenAI can now use your company's approved tools through Merge for Workforce.
Same identity, access, and audit controls IT already set for every other agent, and they hold even after an employee closes the app.
merge.dev/blog/bring-dots-to…
Next week, Oct 28th, @merge_api is teaming up with @FoundHerHouse and Harvard Undergraduate Women in Entrepreneurship for a fall happy hour at Russell House Tavern.
If you're around Boston, come say hi!
RSVP: luma.com/merge-ytdz
Shensi Ding retweeted
Two frontier models a few points apart on the Intelligence Index can differ 7x in the tokens they burn per task.
GPT-6 Astra (@OpenAI) scores 52.7 and finishes an average Artificial Analysis Intelligence Index task in 27K output tokens. Claude Sonnet 5.5 scores 56.0 and uses 197K. GPT-6.1 Sol comes in at 38K, while Muse Spark 1.3, Gemini 4 Argon and MiMo-V2.6-Pro all land between 60K and 64K.
Output tokens are what you pay for. Sending simple requests to a leaner model is one of the easiest ways to cut inference spend, and Merge Gateway routes them for you.
Scores via artificialanalysis.ai, week of Oct 5.
Shensi Ding retweeted
The two top models on the Intelligence Index take about twice as long per task: Claude Opus 5.5 and Sonnet 5.5 (@AnthropicAI) vs. Muse Wonder (@Meta).
Muse Wonder finishes an average task in 6.8 minutes with a 52.4 score. Opus 5.5 takes 13.2 and Sonnet 5.5 takes 15.3, scoring 57.6 and 56.0. Muse Spark 1.3 and GPT-6 Astra (@OpenAI) follow at 8.1.
When someone is waiting on the answer, minutes can matter more than a few index points. Merge Gateway lets you send latency-sensitive requests to the fast model and the hard ones to the strong one, behind one endpoint.
Scores via artificialanalysis.ai, week of Oct 12.
Shensi Ding retweeted
New in Merge Unified: Auto-link. Create a linked account directly from credentials you already hold, no reauthorization needed.
Learn more: merge.dev/blog/unified-boots…
Shensi Ding retweeted
The top six open-weights models all come from Chinese labs, led by MiMo-V2.6-Pro (@Xiaomi) at 46.3.
DeepSeek's new V4.1 Flash 1017 is right behind at 45.1, then Z AI's GLM-5.3 (44.8), StepFun's Step 5 Preview (43.7), and Kimi K3 (43.6). Meta's Muse Spark Open (@Meta) lands further back at 38.9.
Open weights mean you can run them on your own infrastructure. Merge Gateway routes to self-hosted models alongside hosted ones, behind one endpoint.
Scores via artificialanalysis.ai, week of Oct 19.
Shensi Ding retweeted
MERGE IS HIRING
i've been at merge for almost 4 years, and it has been a wild ride.
we're hiring in sf, nyc and berlin!
check out the roles here: merge.dev/careers
Shensi Ding retweeted
Waitlist for our Vercel Ship afterparty tn is 1k+ long somehow🥹
Who needs a spot?
Post-ship plans: merge x @linear x @supabase afterparty 🎉 at campus (right by the palace of fine arts)
food, drinks, good people
Run it back sf!! luma.com/merge-y2z6
Shensi Ding retweeted
Say hello to eight new connectors in @merge_api!
- Amazon Seller Central (@amazon)
- Plaid (@Plaid)
- Zoho Books (@Zoho)
- Zoho Cliq (@Zoho)
- Ticketmaster (@Ticketmaster)
- RingCentral (@RingCentral)
- Iterable (@Iterable)
- Namespace (@namespacelabs)
We used to watch migrations die waiting on customer reauth. Auto-link skips it: hand us a credential you already have, and the account's onboarded instantly, no reconnect needed.
Read more: merge.dev/unified-api
Shensi Ding retweeted
We just got ranked again on @Paraformtalent's Talent Density Index alongside, @AnthropicAI, @OpenAI, and @ThinkyMachines.
Everyone at Merge owns real problems, and the bar keeps going up because the people you work next to keep raising it!
Thank you to the team and if you want to grow with us, we're hiring.
paraform.com/talent-density-…
congrats to the @labelbox team!! @merge_api is honored to be powering your connectors.
xitter.cf/labelbox/status/211040…
Today we’re announcing our Series E.
We’ve raised $100M+ led by Infinitum Partners. We believe every company will soon run on agents that learn from their own work.
- For frontier labs, Horizon provides RL environments that teach frontier models to do real work.
- For enterprises, Recursion brings managed agents into the apps your teams already use, improving with every run.
labelbox.com/blog/labelbox-s…
Shensi Ding retweeted
The Clef models are now available on @merge_api 🧡
Clef, the new decision model family from Cloudflare (@Cloudflare), is now available on Merge Gateway.
Clef-flash answers in a median 39ms, and in Cloudflare's tests Clef came out ahead of Jev on 3 of 4 workflow evals.
Use it to route a ticket, flag a risky upload or pick an agent's next step, all faster than you can blink.
Try it out: gateway.merge.dev
Shensi Ding retweeted
Ask an agent "which customers were upset last week?" and a few MCP servers won't get you there. Live API lookups can't search across that much data.
At the AI Engineer World's Fair, Gil Feig (@GilFeig) walked through how to build a context graph that syncs data for semantic search and keeps live calls for simple lookups.
youtube.com/watch?v=cSz7aL2n…
Shensi Ding retweeted
Clef, the new decision model family from Cloudflare (@Cloudflare), is now available on Merge Gateway.
Clef-flash answers in a median 39ms, and in Cloudflare's tests Clef came out ahead of Jev on 3 of 4 workflow evals.
Use it to route a ticket, flag a risky upload or pick an agent's next step, all faster than you can blink.
Try it out: gateway.merge.dev
Shensi Ding retweeted
muse wonder is super fast and token efficient ⚡️ ⚡️
give it a go!
The two top models on the Intelligence Index take about twice as long per task: Claude Opus 5.5 and Sonnet 5.5 (@AnthropicAI) vs. Muse Wonder (@Meta).
Muse Wonder finishes an average task in 6.8 minutes with a 52.4 score. Opus 5.5 takes 13.2 and Sonnet 5.5 takes 15.3, scoring 57.6 and 56.0. Muse Spark 1.3 and GPT-6 Astra (@OpenAI) follow at 8.1.
When someone is waiting on the answer, minutes can matter more than a few index points. Merge Gateway lets you send latency-sensitive requests to the fast model and the hard ones to the strong one, behind one endpoint.
Scores via artificialanalysis.ai, week of Oct 12.