Future AGI AI Evaluation SDK

Future AGI AI Evaluation SDK is an open-source platform for evaluating, optimizing, monitoring, and protecting AI agents. Its evaluation options include heuristic, code-based, LLM-as-judge, and agentic methods, with templates and CI/CD support. The traceAI instrumentation converts LLM calls, tool use, retrieval, and chain steps into OpenTelemetry spans. Simulation supports text and voice testing with personas and scenarios; the free plan includes 1M text simulation tokens and 60 voice minutes per month. The integrations page lists 79 integrations and SDK packages for Python, TypeScript, and Java, with featured connections such as OpenAI, Anthropic, Google GenAI, Vertex AI, AWS Bedrock, and Azure OpenAI. The Apache 2.0 platform offers Docker and SDK self-hosting options. Future AGI says Docker Compose self-hosting keeps traces, datasets, evaluations, and model calls within the customer’s network. Enterprise deployment options include managed cloud, private cloud in a customer’s AWS, GCP, or Azure account, and air-gapped on-premise deployment. Free usage pauses at its cap; pay-as-you-go usage continues and can incur overage charges.

Future AGI combines evaluation, tracing, and simulation tools for teams working with AI agents. Review the free-plan cap and retention period, or consider the paid options if ongoing usage and longer retention are priorities.

The platform is presented for startup and enterprise teams building and operating AI agents. It may suit teams that need agent evaluations, tracing, simulation, or self-hosting options.

Future AGI AI Evaluation SDK gives teams building AI agents a combined toolkit for evaluation, tracing, and simulation. It suits developers who want to keep those workflows together, including teams that need to self-host. Its broad coverage is useful, though free usage pauses at the plan cap and longer retention costs more.

Overview

Future AGI positions its platform around the full agent lifecycle: testing behavior, following activity through traces, simulating interactions, and protecting and optimizing agents. That breadth can reduce the need to piece together separate evaluation and observability tools. Teams seeking only a local test runner may find the wider platform more than they need.

Key features

Evaluation and tracing

Evaluations span heuristic rules, code checks, LLM-as-judge assessments, and agentic tests. Templates and CI/CD support make it practical to add checks to a development process, while tool-call checks, safety evaluations, and regression runs address changes that can affect an agent's behavior across steps.

TraceAI turns LLM calls, tool use, retrieval, and chain steps into OpenTelemetry spans. This gives teams a view of how work moves through an agent workflow. The integrations catalog covers 79 integrations, with SDK packages for Python, TypeScript, and Java. Featured providers include OpenAI, Anthropic, Google GenAI, Vertex AI, AWS Bedrock, and Azure OpenAI.

Simulation and deployment

Text and voice simulations use personas and scenarios, extending evaluation beyond fixed checks. The Free plan provides 1M text simulation tokens and 60 voice minutes monthly, a useful starting allowance but a real ceiling for frequent or large-scale runs.

The platform is Apache 2.0 licensed, with Docker, Python SDK, and Node SDK self-hosting options. Future AGI says its Docker Compose deployment keeps traces, datasets, evaluations, and model calls inside the customer's network. That is a meaningful option for teams with data-location constraints. Enterprise deployment also includes managed cloud, private cloud in a customer's AWS, GCP, or Azure account, and air-gapped on-premise deployment.

Pricing

Free — $0/month. The plan includes 50 GB storage monthly, 2K AI credits monthly, 100K gateway requests monthly, 100K cache hits monthly, the simulation allowances, 30-day retention, and community support. The cap pauses usage when reached, so teams relying on continuous evaluations should account for interruptions.

Pay-as-you-go — starts at $0/mo + usage. It includes the Free features, usage-based billing after the free tier, volume discounts at scale, 30-day retention, email support, billing alerts, and spending caps. Usage continues beyond the free allowance but incurs overage charges. This is the flexible step up for variable workloads, though it does not extend retention.

Boost — $250/mo. Boost raises retention to 90 days and adds 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 fits teams that need governance and a longer review window without the Scale tier's workflow and identity features.

Scale — $750/mo. It includes Boost, one-year retention, unlimited queues and monitors, review workflows, inter-annotator agreement, a HIPAA BAA, SAML SSO with SCIM, a 99.9% SLA, 24-hour email support, and a Slack channel. This is the clearer fit for larger evaluation programs with formal review and access-management needs.

Enterprise — $2,000/mo. It includes Scale plus custom retention, ABAC, data masking, a dedicated support engineer and customer success manager, training, architecture review, a financial SLA, and custom rate limits. Organizations needing tailored controls and support have a defined tier; teams without those needs may be paying for capabilities they will not use.

Platforms

Future AGI supports API, Linux, macOS, Windows, web, and self-hosted use. That range gives teams a choice between hosted workflows and deployments they operate within their own environment.

Who it's for

The product is aimed at startups and enterprise teams building and operating AI agents. It is strongest for teams that need several evaluation methods, trace-level visibility, and text or voice simulation in one platform. The free tier is suitable for trying those workflows and smaller workloads; teams that cannot tolerate a cap-induced pause should use pay-as-you-go or a paid plan.

Pros and cons

• Pros: Multiple evaluation methods, CI/CD support, regression checks, and safety and tool-call evaluations cover more than basic prompt scoring.
• Pros: OpenTelemetry spans, a broad integration catalog, and SDKs for three languages support agent workflows across common providers.
• Pros: Simulation includes both text and voice, and self-hosting keeps key data within the customer's network.
• Cons: Free usage pauses at its cap, which can interrupt ongoing work; pay-as-you-go continues only with usage charges.
• Cons: Free and pay-as-you-go retain data for 30 days, so teams needing longer history must move to Boost or above.
• Cons: Formal identity controls, stronger SLAs, and extended support are reserved for higher-priced plans.

Alternatives

For a broader comparison, see AI Agent Evaluation Tools. Choose Arklex if an open-source agent testing framework and free, self-hosted options are the priority. Noveum is another freemium option, with a free plan that includes 2.5K credits, 1M spans, 2 GB storage, three members, and 30-day retention.

AgentClash may suit teams looking for a free evaluation setup centered on 25 monthly runs, up to four models per run, and seven-day replay retention. Pick Braintrust if its free Starter allowance of 1 GB processed data, 10,000 scores, 14-day retention, unlimited users, projects, and datasets better matches the workload.

DeepEval is a free, Apache 2.0 local and CI/CD test runner for teams focused on an open-source evaluation framework. Galileo offers a $100/month Pro plan, billed yearly, with 50,000 traces monthly, standard RBAC, advanced analytics, and Slack support.

Giskard is a freemium alternative with an open-source library, local deployment, and basic LLM vulnerability scanning and RAG evaluation. Google Cloud Agent Evaluation is a paid option with a free trial and usage-based charges for computation-based metrics.

Verdict

Future AGI AI Evaluation SDK is a strong choice for agent teams that want evaluation, tracing, and simulation together, especially when self-hosting or enterprise deployment controls matter. Its range of checks and integrations is compelling, but the free cap can halt usage and the shortest retention tiers keep only 30 days of data. Choose it if those limits fit your workload; look elsewhere if you need a narrowly scoped local runner or uninterrupted free usage.