updated website https://t.co/VPD6JhfqJz
updated docs https://t.co/1lX1tT6iPl
$SERV is getting ready for more
production ready docs give builders the confidence to start.. the flywheel can begin
so much more coming for SERV reasoning.. π
@openservai
Ignore the US, fastest growing credit market is in east africa and $SERV team is already on it
@open_founder teasing banking partnerships, NDAs clearing soon? π§
With the early success of SERV Reasoning in private beta, we are accelerating adoption across two strategic domains.
Larger institutions. Global scale.
This week, our leadership team is in Nairobi meeting with some of the largest banks in the region. Conversations are taking place inside executive boardrooms at Tier 1 institutions with over $7 billion in collective assets under management, with heads of corporate credit, IT, and risk among the participants.
East Africa is the fastest-growing credit market in the world, and Kenya sits at the center of it. As banks across emerging markets look to adopt AI, the opportunity is clear. Major bottlenecks and outdated processes are waiting to be solved, and the institutions that solve them will define how credit operates in the next decade.
For financial institutions, AI adoption only happens when the technology clears a specific bar. Auditable outputs. Reliable performance. Sustainable cost. Most previous attempts at AI integration in this space have stalled on one of those three, often on all of them.
SERV Reasoning was built for exactly this category of buyer. The institutions that cannot afford to be wrong on reliability, cannot afford to be wrong on cost, and require auditability at every step.
Product is only one side of enterprise adoption. Distribution is the other. In financial services, particularly in emerging markets, sales cycles are long, trust is earned through relationships, and adoption depends on being in the right rooms with the right stakeholders.
This is why being on the ground matters. SERV is being positioned not just as a product but as the reasoning layer the next generation of global financial institutions will run on.
The infrastructure layer for enterprise AI is being built in the rooms where the decisions get made.
Another team that decided to switch to SERV.
TRECC is an infra layer for the AI economy that handles credit allocation & risk decisions.
The benchmarks were clear:
β ~0.5s inference speed
β 100% reliability
β 10x more efficient than their previous stack
SERV is inevitable.
lots of people think $SERV is an AI model, but that's wrong..
it's a reasoning layer you can add to any LLM call π€
boosting reliability & speed ποΈ
in a bounded reasoning setup, at a fraction of the cost!
@openservai
BETTER just announced MESHROUTER π
compatible with any model, verifiable attestation of private processing, nobody can read your prompt except you.
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@ole_eth glad youre not giving up, people underestimate what you learn by going through this! doesnt mean you wont make the same mistakes.. in the same boat here, hoping I learned enough this time π