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AI-Flow.eu vs debate.tellodb

AI-Flow.eu and debate.tellodb are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AI-Flow.eu

AI-Flow.eu

The platform connects to SharePoint and company documents, runs retrieval-augmented generation with citations, and lets teams deploy multiple AI assistants across departments without standing up infrastructure. Agents can be chained so that what one step returns routes the next — internal Q&A, document summarisation, and workflow triggers all run on the same canvas. The compliance and audit features are the differentiator for regulated industries: answers trace back to source documents, which matters when legal or finance needs to verify what the assistant said. The ceiling appears when workflows demand branching logic that the visual builder cannot express, at which point teams add custom scripting and are suddenly maintaining two layers. No self-hosted option outside enterprise conversations means your data leaves your building on their terms unless you negotiate otherwise.

debate.tellodb

debate.tellodb

The core mechanism is fact supersession: when a user moves from NYC to SF, TelloDB marks the old location as stale and filters it from active agent context — so the LLM never hallucinates a two-year-old truth. A hybrid HNSW vector plus BM25 search index handles recall, while a separate Metric Vault layer resolves numeric queries deterministically before they ever reach the LLM. The vendor reports p99 retrieval at 4.2ms and benchmarks recall precision above 95% on LongMemEval-S against 68% for standard RAG. The engine ships as a single Rust binary, self-hostable or deployable on the vendor's platform. At v0.1.0, the surface area is narrow — this is a memory layer, not a full agent runtime.

AttributeAI-Flow.eudebate.tellodb
PricingPaidPaid
Price€19/month
Free trial30 daysNo
Open sourceNoNo
Has APIYesYes
Self-hosted optionNoYes
PlatformsWebSelf-hosted binary, platform deployment
Pros
  • Source-cited RAG answers tied directly to SharePoint and uploaded documents, which means users can verify every response and compliance teams have an audit trail instead of having to trust the model's memory.
  • Multi-agent workflow support so a retrieval step, a summarisation step, and a routing step can be chained together — teams avoid stitching these together with separate tools and separate API keys.
  • European hosting and GDPR-oriented positioning, so data residency requirements that would block a US-hosted alternative do not block this one.
  • Multiple independent AI assistants per account scoped to different teams or knowledge bases, which means the HR assistant and the legal assistant never contaminate each other's retrieval context.
  • Audit and compliance features built into the product, so regulated teams get answer traceability without bolting on a separate logging layer after deployment.
  • Fact supersession automatically marks prior user states as stale when contradicted by new input, so your agent stops confidently telling a user their old address is current.
  • Deterministic aggregation in the Metric Vault resolves count and numeric queries before the LLM sees them, which means you stop relying on the model to do arithmetic over memory and stop getting wrong counts.
  • Hybrid HNSW vector plus BM25 search runs in a single Rust binary, so you avoid stitching together a vector store and a keyword search service as separate infrastructure dependencies.
  • Self-host path with an air-gapped proxy gateway option, so teams with data residency requirements can run the memory layer inside their own perimeter without routing user data through a third-party hosted service.
  • Distillation pipeline extracts structured facts from raw conversational text rather than storing full transcripts, which means context windows stay narrow and you are not paying to re-embed every filler word.
Cons
  • Visual agent builder hits its limit when workflows need more than two or three conditional branches based on what a previous step returned — teams building complex decision trees end up adding a scripting layer, which means they are now debugging two systems instead of one.
  • No self-hosted deployment option is available without an enterprise negotiation and no public container or download path exists, so teams in industries where data cannot leave on-premises infrastructure cannot use the standard product at all and must open a sales conversation before writing a single workflow.
  • The tool is a closed, paid-only SaaS with no open-source core, which means teams that hit a capability ceiling cannot fork or extend the platform — they switch to an open-source RAG framework like Dify or LlamaIndex-based stacks and rebuild.
  • TelloDB is a memory substrate only — it provides no agent task planning, tool-calling scaffolding, or workflow logic. Teams that need a full agent runtime will integrate TelloDB as a dependency inside a separate framework (LangGraph, CrewAI, or similar), which means owning the glue code and debugging across two systems when memory retrieval and task execution diverge.
  • The project is at v0.1.0 with the open-source release flagged as new. The knowledge graph engine and temporal truth decay subsystems are advertised but lack the community-tested surface area of established memory stores. Teams building production agents that cannot tolerate evolving APIs will hit breaking changes before the interface stabilizes.
  • Fact supersession logic is deterministic by design, which works cleanly for discrete facts like location or ownership — but nuanced preference evolution ("I mostly still like coffee but only in the mornings now") requires the application layer to model partial invalidation explicitly. Teams handling ambiguous or graduated state changes find themselves writing conflict-resolution logic that the engine does not provide out of the box, at which point simpler alternatives backed by relational stores start looking more tractable.
Bottom line

AI-Flow.eu and debate.tellodb are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between AI-Flow.eu and debate.tellodb?

AI-Flow.eu is Paid, while debate.tellodb is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AI-Flow.eu better than debate.tellodb?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

AI-Flow.eu vs debate.tellodb: which should I pick?

Pick AI-Flow.eu if its pricing model, openness, or platform fit matches your constraints; pick debate.tellodb otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.