Logic
Logic turns a plain-English spec into a tested, versioned production AI agent you can call from anywhere.
Logic's durable selling point isn't the 60-second demo, it's that evals, versioning, rollback, and execution logging sit in the same place you write the agent — so you're not assembling Braintrust plus a prompt registry plus a custom frontend just to ship a classifier. Teams that need to point every step at a hand-picked model, or run in their own VPC, should look elsewhere. If you're fine with Logic picking the model per request, the Free tier is a genuinely low-risk way to test that bet.
Verified 4d ago · liveness 80/100 · cite: rightaichoice.com/tools/logic
- Engineering teams that want evals, versioning, and rollback in the same tool they write agents in
- Marketplaces and ops teams running high-volume moderation, classification, or document extraction
- Product teams where non-engineers update agent behavior through approval workflows instead of redeploys
- Regulated orgs needing SOC 2 Type II, full audit trails, and HIPAA support with a BAA
- Teams that need token-level prompt control and a hand-picked model for every step — Logic chooses the model per request
- Anyone requiring self-hosted, on-premise, or VPC deployment — Logic is a cloud platform
- Simple chatbots that don't need structured outputs, test suites, or version control
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Skip Logic if you need to pin a specific model and hand-tune prompts for every step, or if your security posture requires self-hosted or on-premise deployment — Logic is cloud-only and routes model selection for you.
Overage on Pro and Scale bills at $1 per 1.4M tokens past the included 70M or 430M monthly tokens, which bites once agent traffic grows.
The $0/mo Free tier (15M one-time tokens, 5 agents) fits prototyping; $49/mo Pro (70M tokens/mo, unlimited agents) is the realistic floor for a team running agents in production; $299/mo Scale (430M tokens/mo, SSO/SCIM, 90-day retention) is where regulated teams land. Because all tiers include unlimited seats, Logic undercuts per-seat eval and prompt-management stacks you'd otherwise buy alongside a framework — but a heavy-thinking-model workload can outrun 70M tokens and start paying $1 per
In short
Logic — Logic turns a plain-English spec into a tested, versioned production AI agent you can call from anywhere. Best for Engineering teams that want evals, versioning, and rollback in the same tool they write agents in, Marketplaces and ops teams running high-volume moderation, classification, or document extraction, Product teams where non-engineers update agent behavior through approval workflows instead of redeploys. Free to start; paid plans from $49/mo.
What's new in Logic
Checked 4 days agoAcross the latest 5 updates: 5 news mentions.
AI-powered product categorization and tagging - August 2026
Guide on automating product categorization and tagging with AI to fix poor product data at scale.
What are evals in AI? Engineering team guide (August 2026)
Guide to AI evals covering the metrics that matter for agents and how to wire eval gates into release pipelines.
Safe prompt iteration in production: Versioning guide (August 2026)
Covers bundling, testing, and rolling back LLM prompt versions with regression gates, canaries, and drift monitoring.
Automated prior authorization: faster approvals (August 2026)
Explains how automated prior authorization cuts manual work and speeds approvals, with rollout guidance.
Financial document extraction with AI on Logic (August 2026)
Guide to AI financial data extraction pipelines covering schema enforcement and SEC 17a-4 compliance.
What people actually say about Logic — is it worth it?
We scanned public community sources for Logic on Aug 19, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Logic? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Generate production agents from plain-English specs — no frameworks or SDKs
- Built-in test harness with inline test cases and expected-output matching
- Automatic regression detection on every spec edit
- Synthetic test generation and custom test cases
- CI/CD integration via API for automated eval pipelines
- Git-like version control with diffs and one-click rollback
- Immutable agent versions with version pinning
- Approval workflows for non-technical spec editors
- Expose any agent as a strictly typed REST API on save
- Auto-generated API docs and integration guides
- Auto-generated shareable web app with input forms
- MCP server for Claude, Cursor, and ChatGPT
- Per-agent email trigger and agent tools (email, HTTP)
- Batch processing: run an agent against an entire CSV dataset
- Intelligent model routing across OpenAI, Anthropic, Google, and Perplexity
About Logic
Logic is a spec-driven agent platform: you write what the agent should do, what goes in, and what comes out in plain English, and Logic compiles that spec into a deployed agent — the vendor claims 60 seconds from spec to running agent. No frameworks, no SDKs. Pick a template like PII Redactor, Contract Clause Analyzer, Invoice & PO Data Extractor, Resume Screener, Entity Matcher, or Product Listing Moderator, or fork one and write your own. Each saved agent exposes itself as a strictly typed REST API with auto-generated docs, a shareable web app with input forms, a per-agent email trigger, an MCP server for Claude, Cursor, and ChatGPT, and a CSV batch runner. Logic handles the plumbing you would otherwise assemble yourself: routing each request across OpenAI, Anthropic, Google, and Perplexity by task complexity, latency, and cost, automatic provider failover, and execution caching for deterministic workloads. It takes 130+ multimodal input types and supports web research, PDF form filling, image creation and editing, and a knowledge library. Testing and versioning are built in rather than bolted on. An inline test harness runs on every save against expected outputs, flags regressions, and hooks into CI/CD through the API; synthetic test generation fills gaps. Specs get git-like version control with diffs, immutable versions, version pinning, one-click rollback, and approval workflows so non-engineers can propose changes without a redeploy. Full execution logging captures inputs, outputs, model reasoning, latency, and errors across every agent version. The fit is engineering teams shipping LLM workflows they have to keep running, plus the product and ops colleagues who need to change agent behavior without touching a prompt file. Pricing is usage-based with unlimited users on every tier. It suits teams that want a managed pipeline with evals, versioning, and observability already inside; the tradeoffs are token-level prompt control and self-hosted deployment.
Behind the Verdict
We'd reach for Logic when the agent is a business process rather than a chat toy. Product moderation, invoice extraction, resume screening, contract clause flagging — work that runs thousands of times a month, has a right answer you can write down, and breaks loudly when someone edits a prompt. That's the shape the platform is built around: expected outputs, regression detection, immutable versions, one-click rollback. The money question is token control. Logic routes by task complexity, latency, and cost across OpenAI, Anthropic, Google, and Perplexity, and you don't pick the model per step. For most structured extraction and classification work that's fine, and the caching and failover are things you'd otherwise build yourself. For a multi-stage agent where a specific reasoning model is the whole point, it will feel like a straitjacket. Compared with stitching LangGraph plus Braintrust plus Langfuse plus a hand-rolled FastAPI wrapper, you give up some ceiling and gain a lot of floor. Our take: the eval-and-versioning layer is the reason to buy, the spec-to-agent speed is the reason to try it this week. On pricing, seats aren't the constraint — every tier is unlimited users. Pro at $49/mo includes 70M tokens a month, and overages bill at $1 per 1.4M tokens; Free gives you 15M one-time tokens and up to 5 agents. Enterprise adds custom token volumes, SCIM, SSO, HIPAA with a BAA, and a dedicated Slack channel. Note SSO, SCIM, and HIPAA are not on Pro. Where it bites: free-tier log retention is 7 days and file storage is 10 MB, so don't debug in production on Free. Non-engineers can propose spec edits, but the approval workflow still needs a chain of command — set that up before you hand over access. Watch your specialized operation ceilings, too. Even on Scale
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Real-world workflow fit
Concrete scenarios for the personas Logic actually fits — and what changes day-one when you adopt it.
Forks the Support Ticket Classifier template, edits the spec to match their taxonomy, adds inline test cases with expected outputs, and connects the CI/CD API hook so every spec change runs the eval suite before merge.
Outcome: Agent is live as a typed REST endpoint behind their existing queue, with version pinning and one-click rollback if a regression slips through.
Uses the Product Listing Moderator template, tunes approve/reject/escalate policy rules in the spec, and runs the full listing backlog through the CSV batch runner instead of one-by-one.
Outcome: Listing moderation drops to seconds per item — the vendor cites Garmentory at 48 seconds per listing — while policy edits go through an approval workflow instead of a deploy.
Builds a prior-auth document agent on the Scale tier, uses PDF form filling and 130+ multimodal inputs, and relies on the audit trail plus HIPAA BAA for compliance sign-off.
Outcome: Manual prior-auth triage shrinks and the team can show a logged, versioned, SOC 2 Type II path for every automated decision.
Use Cases
- Redact PII from text with detailed reporting on what was found
- Score resumes against job descriptions with transparent fit scoring and evidence
- Extract structured line items from invoices and purchase orders
- Classify and route support tickets by priority, sentiment, and category
- Approve, reject, or escalate product listings against your policy (Garmentory cut product moderation to 48 seconds)
- Match records across systems with a weighted confidence score and field normalization
- Fill multi-page encrypted PDF forms automatically
- Personalize onboarding from signup context with company, role, and industry enrichment
Models Under the Hood
as of 2026-10-17
Limitations
- Free is capped at 15M one-time tokens, up to 5 agents, 10 MB storage, and 7-day log retention.
- Pro at $49/mo includes 70M dedicated tokens per month, unlimited agents, 1 GB storage, 30-day retention, and SOC 2 Type II; Scale at $299/mo includes 430M tokens/mo, 25 GB storage, 90-day retention, SSO/SCIM, and Slack support; both bill overages at $1 per 1.4M tokens.
- Specialized operations carry monthly ceilings — image generation up to 150, research queries up to 42, audio processing up to 85 minutes, document processing up to 85 pages on Free, rising to 4,300 / 1,200 / 2,500 / 2,500 on Scale.
- Actual usage varies by agent complexity, input size, and output size; the vendor's own representative-agent estimates span roughly 360 fast-model runs per month on Free to roughly 10,500 on Scale.
- SSO, SCIM, HIPAA with a BAA, BYOK, and custom data retention policies sit on higher tiers, and there is no self-hosted deployment option.
as of 2026-10-04
Verification history
We have re-verified Logic 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 10 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Logic tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
A developer or small team prototyping its first agents before committing budget — the 5-agent and 15M one-time token ceiling keeps it to evaluation work.
What this tier adds
Starting tier: $0/mo with unlimited users, up to 5 agents, 15M one-time tokens, 10 MB storage, and 7-day log retention.
Pro
$49/mo
Ideal for
A team running a handful of production agents where several people need access but nobody wants per-seat billing.
What this tier adds
Adds 70M dedicated tokens per month, unlimited agents, 1 GB storage, 30-day retention, email support, and SOC 2 Type II for $49/mo.
Scale
$299/mo
Ideal for
An organization running agents across departments, or a regulated team that needs SSO, SCIM, and a 90-day audit window.
What this tier adds
Raises the token pool to 430M/mo, storage to 25 GB, retention to 90 days, and adds SSO, SCIM, Slack support, and hands-on onboarding for $299/mo.
Enterprise
Custom
Ideal for
Large or healthcare organizations needing custom token volumes, HIPAA with a BAA, BYOK, and a dedicated support channel.
What this tier adds
Custom pricing on top of Scale: custom token volumes, SCIM provisioning, SSO, HIPAA compliance with BAA, dedicated Slack channel, and priority feature requests.
Where the pricing makes sense
The company stage and team size where Logic's pricing actually pencils out — and where peers do it cheaper.
The $0/mo Free tier (15M one-time tokens, 5 agents) fits prototyping; $49/mo Pro (70M tokens/mo, unlimited agents) is the realistic floor for a team running agents in production; $299/mo Scale (430M tokens/mo, SSO/SCIM, 90-day retention) is where regulated teams land. Because all tiers include unlimited seats, Logic undercuts per-seat eval and prompt-management stacks you'd otherwise buy alongside a framework — but a heavy-thinking-model workload can outrun 70M tokens and start paying $1 per
Setup time & first value
How long it actually takes to get something useful out of Logic — broken out by persona, not the marketing-page minute.
Template-based agents (PII Redactor, Support Ticket Classifier, Invoice & PO Extractor) can be forked, edited, and saved in minutes — the vendor claims about 60 seconds from spec to deployed agent, and the auto-generated REST API, web UI, and MCP server appear on save. Budget an afternoon, not a week, to wire the CI/CD eval hook and approval workflow. Custom specs with strict schemas, PDF form
Switching to or from Logic
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangChain or CrewAI: rewrite the chain as a plain-English spec, then use inline test cases to reproduce the behavior your existing evals checked.
- →From Braintrust or Promptfoo: port your expected-output test cases into Logic's inline harness and replace the external eval gate with the CI/CD API hook.
- →From PromptLayer or HumanLoop: move prompt variants into spec versions and use diffs, immutable versions, and rollback instead of a separate prompt registry.
- →From LangFuse or LangSmith: switch tracing to Logic's per-execution logging with input/output inspection, latency, and error history across agent versions.
- →From a custom OpenRouter setup: drop the DIY routing layer and let Logic select across OpenAI, Anthropic, Google, and Perplexity with automatic failover.
- ↗To LangChain or CrewAI: rebuild each agent as explicit chains or crews when you need per-step model pinning and token-level prompt control.
- ↗To a self-hosted stack: move inference in-house if your security posture requires on-premise or VPC deployment, which Logic does not offer.
- ↗To a per-seat eval stack (Braintrust plus PromptLayer): split testing and prompt management back into separate tools if you need them decoupled from the agent runtime.
- ↗To OpenAI Assistants or a provider-native agent API: consolidate onto a single model provider when cross-provider routing and failover stop mattering to you.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Logic”, and we withheld 6: 6 could not be judged, because “Logic” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Logic.
Official links
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Featured Head-to-Head Comparisons
Logic vs Spider Cloud
Pick Logic if you need to ship production-grade AI agents from plain-English specs with built-in testing, versioning, and HIPAA compliance. Pick Spider Cloud if your primary need is fast, reliable, and cheap web data extraction for existing agents or RAG pipelines—it's purpose-built for that at $0.03/1k pages. They are complementary: use Spider Cloud to feed data into a Logic agent.
Logic vs Temporal Ai
For teams needing a battle-tested, open-source durable execution engine for complex, fault-tolerant workflows, Temporal AI is the clear choice. For those who want to ship production-ready LLM agents rapidly with built-in evals, versioning, and compliance (especially healthcare), Logic offers a faster path with less operational overhead. Choose by workload type: Temporal for microservices orchestration and long-running processes, Logic for spec-driven agent deployment.
Logic vs Presto Voice
Presto Voice is laser-focused on QSR drive-thru automation with proven revenue lift (up to 6%), making it ideal for chains like Dairy Queen (newest partner). Logic is a general-purpose agent platform for engineering teams that need HIPAA-compliant, production-ready AI agents defined in plain English. Choose Presto if you run a drive-thru; choose Logic if you build custom AI workflows.
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AutoGen Studio
Free, open-source web UI for prototyping multi-agent AI workflows on AutoGen AgentChat — build agent teams without writing code.
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Relevance AI builds enterprise AI agent workforces that run autonomously with built-in evals and governance.
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