Future AGI AI Evaluation SDK

Overview

Future AGI AI Evaluation SDK is an open-source platform for teams building and operating AI agents. It suits developers who want evaluation, tracing, and simulation in one toolkit, especially when they need self-hosting; the main trade-off is that the free tier pauses at its usage cap.

Its breadth is a strength: teams can test agent behavior, inspect traces, and simulate text or voice interactions without assembling separate tools for each task. The SDK is a better fit for teams with ongoing evaluation and observability needs than for someone seeking only a local test runner.

Key features

Evaluation and tracing

Evaluation combines heuristic, code-based, LLM-as-judge, and agentic methods, with templates and CI/CD support. Tool-call checks, safety evaluations, and regression runs make it relevant to teams checking changes across agent workflows, not just isolated model outputs.

TraceAI turns LLM calls, tool use, retrieval, and chain steps into OpenTelemetry spans. That gives teams a way to follow activity across an agent's workflow. The catalog lists 79 integrations; SDK packages cover Python, TypeScript, and Java, with featured provider integrations including OpenAI, Anthropic, Google GenAI, Vertex AI, AWS Bedrock, and Azure OpenAI.

Simulation and deployment

Text and voice simulations use personas and scenarios, which can help teams exercise interactions beyond fixed evaluation cases. Free accounts receive 1M text simulation tokens and 60 voice minutes per month, but teams running frequent or extensive simulations may hit the free usage cap.

The platform is Apache 2.0 licensed and offers Docker, Python SDK, and Node SDK self-hosting options. Its Docker Compose deployment keeps traces, datasets, evaluations, and model calls within the customer's network. Enterprise deployments also include managed cloud, private cloud in a customer's AWS, GCP, or Azure account, and air-gapped on-premise options. The enterprise security portfolio includes SOC 2 Type II, GDPR, HIPAA, ISO 27001, and CCPA; ISO 42001 is in progress.

Pricing

The Free plan costs $0 /month and includes 50 GB storage/mo, 2K AI credits/mo, 100K gateway requests/mo, 100K cache hits/mo, the monthly simulation allowance, 30-day data retention, and community support. It is a useful starting point, but usage pauses at the free cap, so it is not a dependable option for uninterrupted workloads that outgrow the allowance.

Pay-as-you-go starts at $0 /mo + usage. It includes everything in Free, usage-based billing after the free tier, volume discounts at scale, 30-day retention, email support, billing alerts, and spending caps. This suits teams that need usage to continue past the free allowance; the trade-off is overage charges rather than a fixed monthly bill.

Boost costs $250 /mo, adding 90-day retention, five knowledge bases, 10 annotation queues, 15 monitors, SOC 2 Type II, OAuth SSO, audit logs, a 99.5% SLA, and 48-hour email support. It is aimed at teams that need longer retention and governance features, but the queue and monitor limits matter for larger review operations.

Scale costs $750 /mo and includes everything in Boost, one-year retention, unlimited queues and monitors, review workflow, inter-annotator agreement, HIPAA BAA, SAML SSO plus SCIM, a 99.9% SLA, 24-hour email support, and a Slack channel. It is the more suitable tier for larger teams with formal review and identity-management needs; the higher price buys materially broader capacity and support.

Enterprise costs $2,000 /mo and includes everything in Scale, custom retention, ABAC, data masking, a dedicated support engineer and CSM, training, architecture review, a financial SLA, and custom rate limits. It is designed for organizations with deployment, security, or service requirements beyond the standard tiers, not cost-conscious small teams.

Platforms

Future AGI supports API, Linux, macOS, self-hosted, web, and Windows. The mix of hosted access and self-hosting is useful for teams that need deployment flexibility, including organizations that keep agent data within their own network.

Who it's for

Startups can begin with capped free usage or move to pay-as-you-go as demand grows. Teams operating agents at scale have clearer reasons to consider Boost or Scale, where retention, SSO, review capacity, SLAs, and support expand. Organizations with strict control or custom service needs can assess Enterprise and its private-cloud or air-gapped deployment options.

It is less compelling for a developer who only wants a lightweight local evaluation runner: the platform's advantage is the combination of evaluation, observability, simulation, and deployment choices.

Pros and cons

• Pro: Multiple evaluation methods, regression runs, safety checks, and tool-call checks cover varied agent testing needs.
• Pro: OpenTelemetry-based tracing and a broad integrations catalog connect evaluation with workflow observability.
• Pro: Self-hosting and private or air-gapped enterprise deployments give teams meaningful control over where data stays.
• Con: Free usage pauses at its cap, so growing workloads must move to usage billing or a paid tier to continue.
• Con: Boost and higher plans add significant monthly costs; smaller teams may not need their retention, governance, or support features.

Alternatives

AI Agent Evaluation Tools is the category list for comparing options across the field.

• W&B Weave is a reasonable alternative for teams seeking a free tier with evaluations, tracing, and scorers; its free plan has 1 GB/mo of data ingestion and 5 GB/mo of storage.
• DeepEval is the better fit for developers who want an Apache 2.0 open-source evaluation framework designed to run locally and in CI/CD.
• Noveum is another freemium option, with a free plan that includes 2.5K credits/mo, 1M spans/mo, 2 GB storage, three members, and 30-day retention.
• Promptfoo may suit teams prioritizing local or self-hosted evaluation and red-team testing; its Community plan includes 10k red-team probes/month.
• Opik is an alternative when running open-source observability and evaluation code locally is a priority.
• AgentClash may suit a small team that can work within one workspace, 25 eval runs per month, and up to four models per run on its free plan.
• Tangle is another freemium option; its free plan requires prepaid credit before using AI models.
• Braintrust is an alternative with a free Starter plan that includes 1 GB processed data, 10,000 scores, 14-day retention, and unlimited users, projects, and datasets.

Verdict

Future AGI is a strong choice for teams that want agent evaluation, tracing, simulation, and self-hosting options under one roof. Its breadth and deployment flexibility are the main reasons to choose it; look elsewhere if you need only a lean local evaluator or cannot accept free-tier pauses and usage-based charges as workloads grow.