AI take on Toloka
Toloka stands out for agent trajectories and RL environments, but the managed-service model demands procurement tolerance and careful contracting.
AI Infrastructure & APIs comparison · 2026
Toloka vs Zep
Compare Toloka and Zep as AI Infrastructure & APIs tools on fit, pricing, and the capabilities that actually overlap in 2026. Pick Toloka for teams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learning. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.
Updated Aug 23, 2026
Expert-curated training, evaluation and red-teaming data for AI agents and LLMs
Starts at Custom quote (contact form budget bands start at under $25k)·AI Infrastructure & APIs
Agent memory at enterprise scale, built on temporal context graphs
Starts at $0/month·AI Infrastructure & APIs
At a glance
TolokaZep
CategoryAI Infrastructure & APIsAI Infrastructure & APIs
PricingStarts at Custom quote (contact form budget bands start at under $25k)Starts at $0/month
Free tierNoYes
PlatformsWebWeb
Suitable forTeams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learningTeams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
CompanyToloka Group, Inc.Zep AI, Inc.
Founded20142023
How they differ
Shared AI Infrastructure & APIs rubric, filled from each listing. Not a score.
Model catalog
TolokaZep
Text modelsNot publishedNo
Image modelsNot publishedNo
Video modelsNot publishedNo
Speech modelsNot publishedNo
Open-weight modelsNot publishedNo
Pinned versionsNot publishedNot published
Serving
TolokaZep
One unified APINot publishedNo
OpenAI-compatible APINot publishedNo
Streaming responsesNot publishedNot published
Batch jobsNot publishedNot published
Provider fallbackNot publishedNot published
Published rate limitsNot publishedNot published
Build & tune
TolokaZep
Fine-tuningYesNot published
EmbeddingsNot publishedNot published
Vector storeNot publishedNot published
RAG pipelinesNot publishedLimited
Agent frameworkYesNo
Tool / function callingNot publishedLimited
Observe & control
TolokaZep
Usage dashboardNot publishedYes
Per-request costsNot publishedNot published
Traces / loggingNot publishedYes
EvalsYesNo
Prompt managementNot publishedNot published
Zero-retention optionNot publishedLimited
Access
TolokaZep
Public APINot publishedYes
Official SDKNot publishedYes
Self-serve signupNot publishedYes
Free trialNot publishedNot published
Team workspaceNot publishedNot published
SSO / SAMLNot publishedNot published
Mobile appsNot publishedNo
Browser extensionNot publishedNo
Self-host / on-premNot publishedYes
Commercial
TolokaZep
Commercial licenseNot publishedNot published
Usage-based pricingNot publishedNot published
Invoice / PONot publishedNot published
SOC 2Not publishedYes
GDPR / DPANot publishedNot published
Audit logNot publishedYes
Role-based accessNot publishedLimited
Features
These listings describe different capabilities. What each one ships:
Only Toloka
- Environments generation: context-rich simulated environments for evaluating and training agents
- Training datasets covering specialized agentic skills
- Evaluation and red-teaming that assesses agent performance and identifies vulnerabilities
- Agent trajectory demonstrations and step-by-step evaluations across tool-use workflows
- Virtual environments and RL-gyms with MCP replicas and computer-use testbeds
- Safety red-teaming for injection vulnerabilities and policy compliance
- Demonstrations generation for Supervised Fine-Tuning (SFT)
- Preference collection for RLHF and Direct Preference Optimization (DPO)
Only Zep
- Temporal context graphs that record facts with a validity window
- Fact invalidation when new information contradicts the graph, with old facts kept as history
- Point-in-time queries: ask what is true now or what was true on a past date
- Multi-source ingest from chat history, business data (JSON) and user interactions
- Automated context assembly returning token-efficient context blocks
- Observations: patterns, recurrences and co-occurrences detected across the graph
- Provenance on every fact, traced back to the source episode
- Context Lake architecture governing millions of context graphs as one system
Use cases
These listings describe different use cases. What each one ships:
Only Toloka
- Producing agent trajectory data to post-train tool-using and computer-use agents
- Building RL gym environments with MCP replicas for agent evaluation and reinforcement learning
- Collecting human preference pairs for RLHF and DPO alignment runs
- Red-teaming assistants for prompt injection vulnerabilities and policy compliance
- Generating repository-scale programming data for AI coding copilots
- Sourcing domain-expert reasoning chains in regulated fields such as medicine and law
- Running customized human evaluation of model outputs across text, image, video and audio
- Licensing off-the-shelf datasets such as University-level Math Reasoning to bootstrap a benchmark
Only Zep
- Giving a production customer-support agent persistent memory of a user's prior issues and stated preferences
- Fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
- Answering point-in-time questions such as what a customer's plan or preference was on a specific date
- Reducing prompt token spend by replacing full chat transcripts with an assembled context block
- Auditing why an agent said something by tracing the underlying fact back to its source episode
- Detecting behavioural patterns, such as repeat upgrade timing, and feeding them to an agent as Observations
- Running agent memory inside a regulated customer's own VPC via Bring Your Own Cloud
- Exposing agent memory to IDEs and assistants through the Memory MCP Server
Plans
Toloka
Custom data engagement Custom quote/mo or Custom quote/yr
Toloka publishes no pricing page, plan table or public rate card · Toloka scopes each project through the Talk to us form · Toloka contact form budget bands: under $25k, $25-50k, $50-100k, $100k-200k, $200k+ · Toloka timeline options: within a month, 1-3 months, 3-6 months, just researching · Toloka Terms of Use state that website terms do not govern paid services, which sit under separate terms
Zep
Free $0/mo or $0/yr
10,000 credits per month (no rollover or auto top-up) · 2 projects · Memory MCP Server seat · Custom entity/edge types · Variable rate limits depending on service-wide load · Lower priority Episode processing · Community support
Flex $125/mo or $1250/yr
50,000 credits per month included, then $25 per 10,000 credits · Auto top-up at 20% (10,000 credits / $25) · 30-day credit rollover · 600 requests per minute · 5 projects · 5 Memory MCP Server seats · 10 custom entity/edge types · API logs retained 1 day · Unlimited memories and retrieval users · Community support · Cloud deployment
Flex Plus $375/mo or $3750/yr
200,000 credits per month included, then $75 per 40,000 credits · Auto top-up at 20% (40,000 credits / $75) · 60-day credit rollover · 1,000 requests per minute · 10 projects · 15 Memory MCP Server seats · 20 custom entity/edge types · Observations, custom extraction instructions, webhooks, analytics · API logs retained 7 days · Unlimited memories and retrieval users · Priority support
Toloka strengths
- Toloka documents concrete agent-specific deliverables such as RL-gyms with MCP replicas and computer-use testbeds, not generic labeling
- Toloka names its quality methodology explicitly: post-verification, dynamic overlaps, cross-validation, golden sets, 50+ automated QC methods
- Toloka reports expert coverage across 50+ knowledge domains and 120+ subdomains, useful for medicine, law and other specialized work
- Toloka publishes security posture details including ISO 27001, ISO 27701, SOC 2, GDPR, CCPA and HIPAA compliance plus on-premises storage options
- Toloka sells off-the-shelf datasets and Toloka Arena alongside custom projects, giving smaller teams an entry point
Watch-outs
- Toloka publishes no pricing page, plan table or unit rates, so no cost can be estimated before a sales call
- The Toloka contact form's lowest budget band is under $25k, which signals a project floor unsuitable for small experiments
- Vendor contradiction: the Toloka footer credits Toloka AI BV while the Toloka Terms of Use define Toloka as Toloka Group, Inc. of Wilmington, Delaware, and the privacy notice applies to Toloka AI B.V.
- Vendor contradiction: Toloka's website Terms of Use explicitly state they do not govern paid services, so the terms a buyer actually signs with Toloka are not published
- Toloka work is delivered as a managed service, so buyers cannot self-serve a project without contacting Toloka
- Toloka's Eligibility and Geographic Restrictions policy and terms warn that access may not be lawful in some countries, limiting where contributors and buyers can participate
- Toloka's privacy notice states that contributor names, emails and Slack, Jira or Git handles can appear inside delivered coding task materials shared with clients
- Toloka's website terms cap total liability for site-related claims at US $100, and paid-service liability is negotiated separately
Zep strengths
- Zep publishes concrete p95 latency figures across graph sizes (148ms at 10K to 168ms at 100M) rather than a vague speed claim
- Z
- Temporal context graphs that record facts with a validity window
- Fact invalidation when new information contradicts the graph, with old facts kept as history
- Point-in-time queries: ask what is true now or what was true on a past date
- Multi-source ingest from chat history, business data (JSON) and user interactions
- Automated context assembly returning token-efficient context blocks
- Observations: patterns, recurrences and co-occurrences detected across the graph
Watch-outs
- Zep plan limits come from the published pricing table.
- Zep packaging is recorded from the vendor pages available at analysis time.
Toloka vs Zep verdict
Who each product is for, then labeled AI takes. Not a generic winner.
Bottom line
Pick Toloka for teams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learning. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.
Who Toloka is for
Teams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learning
Expert-curated training, evaluation and red-teaming data for AI agents and LLMs
Who Zep is for
Teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
Agent memory at enterprise scale, built on temporal context graphs
AI take on Zep
As of August 2026, Zep stands out where agent memory must be temporal, governed, and auditable rather than a thin wrapper around transcript retrieval.
Toloka vs Zep FAQ
Common questions when choosing between Toloka and Zep.
Is Toloka or Zep the better AI Infrastructure & APIs tool?
Pick Toloka for teams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learning. Pick Zep for teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query.
Which is cheaper, Toloka or Zep?
Toloka starts at Custom quote (contact form budget bands start at under $25k). Zep starts at $0/month. Confirm current pricing on each vendor site.
Who should choose Toloka?
Teams producing agent trajectory data to post-train tool-using and computer-use agents and building RL gym environments with MCP replicas for agent evaluation and reinforcement learning
Who should choose Zep?
Teams giving a production customer-support agent persistent memory of a user's prior issues and stated preferences and fusing CRM, billing and product-event JSON into a single per-user graph an agent can query
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