Semelbase
Pricing
- Free Tier
- Free audit available
Summary
Every time an agent re-runs a task it already answered last Tuesday, you pay again — and most inference stacks have no memory that it happened. Semelbase is an AI infrastructure proxy built to catch that spend before it leaves your budget.
The vendor positions Semelbase as a ledger and routing layer that sits between your agents and your AI providers, deduplicating inference requests, surfacing usage across teams, and directing traffic to whichever provider fits your cost and budget constraints at that moment. The audit capability gives engineering leads a cross-team view of what is being called, how often, and what it costs — a gap that becomes expensive when five teams are running overlapping agents against the same endpoints. The self-hosted path matters for organizations that cannot route production inference traffic through a third-party cloud. Where this architecture shows strain is in setups with highly dynamic, non-repeatable prompts, where deduplication recovers little and routing optimization becomes the only lever.
Bottom line: Semelbase earns its place when your agents are making repetitive, auditable calls across multiple providers and teams — it becomes hard to justify when your workload is mostly novel, one-off generation where the deduplication layer finds nothing to recover.
Community Performance Report Card
No community ratings yet. Be the first to rate this tool!
Pros
Sign in to edit- Request deduplication at the proxy layer, so identical or near-identical agent calls are served from cache rather than billed again — directly cutting the portion of inference spend that comes from agents repeating resolved work.
- Cross-team usage audit in a single view, so engineering leads can see overlapping inference patterns across agents without manually correlating provider invoices with internal logs.
- Provider routing with budget constraints, so when one provider's costs spike or a budget ceiling approaches, traffic shifts without requiring a config change in every agent individually.
- Self-hosted deployment path, so organizations in regulated environments or with data-residency requirements are not blocked from using the observability and deduplication layer.
- API-accessible architecture, so the proxy layer integrates into existing agent infrastructure without forcing teams to rebuild call patterns from scratch.
Cons
Sign in to edit- Deduplication value collapses when agent prompts are highly dynamic or context-specific: if requests are rarely repeated verbatim, the cache contributes little, and teams are paying for infrastructure overhead without recovering meaningful spend — at that point, a direct provider integration with manual cost tagging is less friction.
- The vendor page provides minimal public documentation on matching logic — specifically, how 'equivalent' requests are identified — which means teams with compliance requirements around data handling inside the proxy layer face an audit gap they have to resolve before deploying in production.
- Advanced inference optimization features are paid-only, so teams that deploy on-prem under the free path and later need budget-based routing in production will hit a commercial gate mid-deployment rather than discovering it at evaluation time.
About
- Platforms
- Docker, web dashboard
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- 2026-08-16T19:47:17.465Z
Best For
Who it's for
- Organizations running multiple AI agents
- Teams tracking and optimizing inference costs
- Enterprises needing on-prem AI observability
What it does well
- Reducing redundant agent inference spend
- Auditing AI usage across teams
- Routing requests to optimal providers with budgets
Integrations
Add notes, reviews, and benchmarks so the next visitor gets a clearer picture.
Compare Semelbase
Spotted incorrect or missing data? Join our community of contributors.
Sign Up to ContributeFrequently Asked Questions
- Is Semelbase free?
- Semelbase has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is Semelbase open source?
- No — Semelbase is a closed-source tool. Source code is not publicly available.
- Does Semelbase have an API?
- Yes. Semelbase exposes a developer API. See the official documentation at https://semelbase.com for details.
- Can I self-host Semelbase?
- Yes. Semelbase supports self-hosting on your own infrastructure.
- When was Semelbase released?
- Semelbase was first released in 2026.
- What platforms does Semelbase support?
- Semelbase is available on: Docker, web dashboard.
Curated lists that include this category
Paying twice for the same agent output
Every time an agent re-runs a task it already answered last Tuesday, you pay again — and most inference stacks have no memory that it happened. Semelbase acts as a ledger and routing layer between agents and AI providers.
How the proxy works
The tool deduplicates inference requests, surfaces usage across teams, and directs traffic to the provider that meets current cost and budget constraints. An audit view gives engineering leads a single picture of what calls are made, how often, and what they cost when five teams run overlapping agents against the same endpoints. Self-hosted deployment keeps production traffic inside the organization.
Where it helps and where it falls short
Request deduplication at the proxy layer serves identical or near-identical calls from cache rather than billing again. Cross-team usage audit reveals overlapping patterns without manual invoice correlation. Provider routing shifts load when one provider’s costs spike or a budget ceiling approaches. The value of deduplication collapses when prompts are highly dynamic and rarely repeat, leaving teams to pay for overhead with little spend recovered. The vendor page gives minimal public detail on how equivalent requests are identified.
Who it is for and who should skip it
Best for organizations running multiple AI agents, teams tracking and optimizing inference costs, and enterprises needing on-prem AI observability. Skip it when agent prompts stay highly dynamic or when compliance requirements demand detailed public documentation on matching logic inside the proxy.