LeanCTX vs YABANIN
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
LeanCTX compared with YABANIN
| Detail | 
LeanCTX | 
YABANIN |
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| What it does | The Context Gateway for AI systems
| Self-hosted AI infrastructure with measurable returns
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| Stage | Not given
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| Founded | Not given
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| Based in | CH
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| Pricing model | Freemium
| Contact for pricing
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| Pricing | Community: Free (open-source, local use). Pro: $9/month or $90/year (personal cloud sync, 1 GB hosted index). Team: $29/month per seat or $290/year per seat (team server, shared workspace, 20 GB index, 1-25 seats). Enterprise: Contact for pricing.
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| Key features | - Source selection and retrieval with task-relevant context at configurable depth
- Access controls via PathJail boundary enforcement and role-based permissions
- Read-time content filters for injection patterns and personal data detection
- Memory and continuity to retain findings and connections across sessions
- Evidence and outcomes recording with source references and usage audit trails
- Integration with AI tools via SDK, MCP, hooks and supported client adapters
- Local, VPC, on-premises and offline deployment options
- Optional production intelligence for planning, ranking and routing enhancements
- SDK with five stable primitives and six Agent Tools language contracts
- Context cache, reference routing and usage accounting
| - Model provider support through a single common gateway
- Usage attribution to teams, tasks, and agents
- Agent workflows in Scala for repositories and code
- Apache-2.0 open-source core with enterprise deployment option
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| What makes it different | - Deterministic, model-agnostic context processing independent of AI provider choice
- Governs context without controlling model calls, keeping AI decisions under user ownership
- Records measurable impact with 64.1% reported context reduction in field use
- Open-source core (Apache 2.0) with commercial tiers for teams and enterprises
- Transparent governance with separate evaluation of task outcome from context delivery
| - Full visibility into AI costs attributed to specific teams, tasks and agents
- Self-hosted deployment keeps data and models under company control
- Model agnostic with support for multiple providers through one gateway
- Structured four-step implementation path with clear ownership and baselines
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 42 ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 3 | 0 |
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| Citation Flow (Majestic) | 35 | 0 |
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| Referring domains (Majestic) | 212 | 0 |
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4 details filled in for both companies.
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