Production agent observability
Trace model calls, retrieval, tools, agent steps, sessions, costs, latency, and failures in one view.
Independent tool overview
Future AGI at a glance
A developer platform for tracing, evaluating, simulating, protecting, and improving production LLM and agent systems.
Visit the official Future AGI site ↗
- Best for
- Engineering teams operating production LLM, RAG, voice, or agent applications
- Core products
- Observe, Evaluate, Command Center, Protect, Simulation, and Falcon AI
- Free tier
- Monthly allowances with no credit card
- Pricing model
- Usage-based after free allowances
- SDKs
- Python and TypeScript, plus tracing support for Java and C#
Overview
What Future AGI is
Future AGI has expanded well beyond automated QA for model outputs. Its current platform covers production tracing and observability, offline and online evaluations, an AI gateway, runtime guardrails, text and voice simulation, datasets, annotations, prompt management, and AI-assisted error analysis.
It is aimed at teams shipping LLM applications, RAG systems, and agents—not people comparing consumer chatbots. The strongest fit is a team that wants evaluation results connected directly to production traces and can define meaningful quality, safety, cost, and task-success metrics.
Use cases
Who Future AGI is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Evaluation-driven releases
Run regression suites in development and CI, then apply continuous or historical evaluations to production traces.
Runtime safety and quality controls
Route traffic through a gateway with guardrails, caching, provider controls, cost tracking, and format validation.
Voice and conversational testing
Simulate text and voice interactions before exposing an agent to real customers.
Capabilities
Core Future AGI features
Observe
Captures traces, spans, sessions, agent graphs, end users, evaluation scores, dashboards, and alerts.
Evaluate
Supports local heuristics, code evaluators, managed LLM-as-judge checks, agentic evaluators, datasets, CI/CD, and production scoring.
Agent Command Center
Provides an AI gateway for model routing, caching, cost tracking, prompt controls, tool calling, and response-format validation.
Protect guardrails
Checks text, image, or audio traffic for issues such as prompt injection, PII, secrets, toxicity, and policy violations, with block, warn, mask, or log actions.
Simulation
Generates text and voice interactions to exercise agents across scenarios before or alongside production use.
Falcon AI analysis
Uses AI credits for error analysis, clustering, insight generation, auto-tagging, reports, and explanations of evaluation results.
Annotations and feedback
Lets human reviewers label traces and datasets, correct evaluator judgments, and feed better examples back into quality workflows.
Open-source SDK stack
Offers evaluation, guardrail, tracing, dataset, prompt, simulation, and optimization libraries, with the platform announced under Apache 2.0.
Process
How the Future AGI workflow works
Step 1
Define success
Choose task-specific metrics and failure thresholds for quality, safety, latency, cost, retrieval, and tool use.
Step 2
Instrument the application
Add the relevant TraceAI integration or custom spans so model calls, retrieval, agent actions, and sessions reach Observe.
Step 3
Build a representative dataset
Combine curated examples, production failures, edge cases, and simulations without exposing unnecessary sensitive data.
Step 4
Run layered evaluations
Use deterministic or local checks first, then add code, managed judge, or agentic evaluations where the extra cost is justified.
Step 5
Gate and monitor releases
Run regression evaluations in CI, use canary or shadow traffic where appropriate, and alert on meaningful production failures.
Step 6
Review and improve
Investigate failed traces, correct bad evaluator judgments, update prompts or application logic, and rerun the same evaluation set.
Cost
Future AGI pricing and free plan
Future AGI starts at $0 with monthly free allowances and no per-seat charge. Pay-as-you-go billing begins only after a team exceeds the included storage, AI-credit, gateway, cache, text-simulation, or voice-simulation allowance.
Free
$0/month
Full-product starter tier with monthly usage allowances and community support.
- 50 GB storage and 30-day data retention
- 2,000 AI credits
- 100,000 gateway requests and 100,000 cache hits
- 1 million text-simulation tokens and 60 voice-simulation minutes
- Unlimited team members and projects
- Usage pauses at the cap
Pay as you go
$0 base + usage
Continues service beyond the free allowances with spending controls and volume discounts.
- Storage starts at $2 per GB above 50 GB
- Managed AI features start at $10 per 1,000 credits above the included 2,000
- Gateway requests start at $5 per 100,000
- Cache hits start at $1 per 100,000
- Text simulation starts at $2 per 1 million tokens
- Voice simulation starts at $0.08 per minute
Enterprise
Custom
Contracted deployment, support, security, compliance, retention, and scale requirements.
- Contact Future AGI for scope and terms
- Protect is documented for Cloud and Enterprise plans
- Confirm region, retention, support, and data controls during evaluation
Pricing checked . Check current pricing at the source ↗
Assessment
Future AGI strengths and limitations
Where it stands out
- Broad platform spanning evaluation, observability, gateway, guardrails, simulation, and human feedback
- Large monthly free allowances with unlimited team members and projects
- Local heuristic and bring-your-own-key evaluations can reduce managed judge cost
- Trace-native workflow connects failures to the exact model, retrieval, and tool steps involved
- SDK coverage supports Python and TypeScript applications plus tracing in Java and C#
- Usage caps and billing limits help control surprise spend
What to consider
- Requires engineering instrumentation and a disciplined evaluation program to deliver value
- Usage-based billing spans several meters and needs active monitoring
- AI-as-judge and agentic evaluators can themselves be inconsistent or biased
- Thirty-day retention on Free and pay-as-you-go may be too short for some audit or regression needs
- Managed analysis, guardrails, and synthetic-data workflows consume shared AI credits
- A broad platform can be more operational overhead than a team needs for simple request logging
- Guardrails reduce risk but do not guarantee a safe or compliant AI system
Compare
Future AGI alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Coding
Helicone
A simpler choice for teams primarily interested in LLM request observability, cost tracking, and gateway workflows.
Explore Helicone →Coding
LangChain
A broader application-development ecosystem when the main need is building agents and chains rather than adopting a dedicated evaluation platform.
Explore LangChain →Sales
Vapi
A more specialized platform for building and operating voice agents, though it does not replace a full evaluation and observability layer.
Explore Vapi →Questions
Future AGI FAQs
What does Future AGI do?
Future AGI helps teams trace, evaluate, simulate, protect, route, and improve LLM and agent applications. It combines observability, evaluations, an AI gateway, guardrails, human annotation, prompt management, and AI-assisted failure analysis.
Is Future AGI free?
Yes. The Free plan requires no credit card and resets monthly with 50 GB of storage, 2,000 AI credits, 100,000 gateway requests, 100,000 cache hits, 1 million text-simulation tokens, and 60 voice-simulation minutes.
What happens when the free allowance is exhausted?
On the Free plan, usage pauses at the cap. With pay-as-you-go enabled, service continues and the account is billed at the published usage rates, with billing alerts and spending caps available.
What are Future AGI AI credits?
AI credits pay for managed AI work such as code and LLM-as-judge evaluations, Protect checks, agentic evaluators, synthetic data, automated annotation, and Falcon AI analysis. Local heuristic evaluations are always free, and BYOK judge calls have no platform AI-credit charge.
Can Future AGI evaluate RAG and agents?
Yes. It supports response, retrieval, trace, session, tool-use, safety, and agent evaluations, along with datasets, production traces, simulation, and CI/CD workflows.
Does Future AGI block unsafe prompts?
Its Protect layer can block, warn, mask, or log traffic based on configured checks for issues such as prompt injection, PII, secrets, and harmful content. Teams still need threat modeling, permissions, testing, incident response, and human oversight.
Is Future AGI open source?
Future AGI announced its platform stack as open source under Apache 2.0 in July 2026. Review the exact repository, package, and deployment coverage for the components you plan to operate yourself.
Bottom line
Our Future AGI verdict
Future AGI is a strong fit for teams that want evaluation, observability, runtime controls, and simulation connected in one production workflow. Its generous free allowances make a pilot practical, but success depends less on installing the SDK than on defining trustworthy metrics and continuously reviewing both agent failures and evaluator mistakes.
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