debate.tellodb vs Gateplex

debate.tellodb and Gateplex 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.

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.

Gateplex

Gateplex is governance middleware: it does not run your agents, it watches them. The vendor describes it as a policy enforcement layer that intercepts agent actions — API calls, approvals, data sends — checks them against defined rules, and blocks or flags violations before execution completes. That distinction matters for regulated environments where post-hoc logging is not enough. The free tier covers three agents and a capped intercept volume per month, which fits a proof-of-concept but runs short the moment a second team deploys. Beyond that ceiling, teams move to a paid tier or hit a wall.

Attribute	debate.tellodb	Gateplex
Pricing	Paid	Paid
Price	—	$199/month
Free trial	No	No
Open source	No	No
Has API	Yes	Yes
Self-hosted option	Yes	No
Platforms	Self-hosted binary, platform deployment	Cloud-based middleware; integrates with agent frameworks on any platform running OpenAI, Anthropic, LangChain, CrewAI, AutoGen, Vertex AI, or AWS Bedrock
Pros	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.	Real-time action interception before execution completes, which means a procurement agent cannot approve an out-of-policy spend and then get flagged about it afterward — the action is stopped in the moment. PII detection at the intercept layer, so customer data does not reach a third-party API before a policy check has cleared it — without this, a misconfigured agent integration becomes a data leak that logging discovers too late. Duplicate transaction detection for financial agents, which prevents a refund or payment from issuing twice due to a retry loop or race condition — the kind of error that is trivial to miss and expensive to reverse. Audit trail output formatted for legal and compliance review rather than raw telemetry, so the evidence package a regulator or procurement committee requests does not require a data engineering sprint to produce. API access to the enforcement layer, which means policy rules can be managed programmatically and integrated into existing deployment pipelines rather than configured only through a UI.
Cons	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.	No self-hosted deployment option is documented — every agent action routed through Gateplex passes through vendor infrastructure. Teams with data residency requirements, air-gapped environments, or legal restrictions on externalizing sensitive financial or health data have no workaround: this is a hard architectural incompatibility, not a configuration problem, and those teams evaluate on-premises alternatives instead. The free tier caps at three agents and a fixed intercept volume per month. A team piloting with two agents clears that ceiling the moment a third team onboards or production traffic spikes — at which point the choice is a paid tier commitment or a freeze on agent expansion, and the evaluation timeline compresses. Gateplex enforces policy on agent actions but does not itself define what your agents should do — teams that want policy logic tightly coupled to agent orchestration (branching based on what a prior step returned, approval gates wired into the agent graph) end up maintaining Gateplex as a separate enforcement layer alongside their orchestration framework, which is two systems to debug when something breaks.

Bottom line

debate.tellodb and Gateplex 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 debate.tellodb and Gateplex?

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

Is debate.tellodb better than Gateplex?

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.