Future AGI - 2026 Pricing, Features, Reviews & Alternatives

Future AGI is an open-source, end-to-end AI agent engineering platform that covers the full agent lifecycle: simulate, evaluate, optimize, observe, protect, and gateway. Available as fully managed SaaS, self-hosted VPC deployment on AWS, GCP, or Azure, air-gapped on-premises, and via AWS Marketplace, it targets engineering teams, product managers, QA teams, and domain experts building and operating LLM-powered applications and AI agents. Core instrumentation libraries are published under Apache 2.0. Python and TypeScript SDKs are available.

The platform consolidates capabilities that typically require separate tools. Simulation tests voice and chat agents against 18 pre-built personas plus unlimited custom personas before deployment. Evaluation runs across datasets using heuristic methods (BLEU, ROUGE, regex), LLM-as-judge, code evaluations, and agentic evaluation agents, backed by 70+ built-in rubrics covering faithfulness, toxicity, hallucination, refusal, sentiment, and bias detection across text, image, audio, and video. The Agent Command Center gateway sits between the application and 100+ LLM providers, handling routing, caching, cost tracking, and observability through a single API with BYOK support. Real-time guardrails screen inputs and outputs at sub-100ms latency across content moderation, bias detection, prompt injection blocking, and PII detection, natively across text, image, and audio. Prompt optimization iterates using six algorithms including Bayesian Search, ProTeGi, and PromptWizard, scoring every candidate before any human-approved deployment.

Future AGI serves regulated industries including healthcare, financial services, insurance, customer services, and logistics, with compliance coverage for SOC 2 Type II, HIPAA, GDPR, CCPA, ISO 27001, and the EU AI Act. Observability includes end-to-end tracing of every LLM call, tool use, and agent decision, with real-time dashboards, 70+ trace filters, session management, AI-powered anomaly alerts, and an Error Feed that clusters agent errors and surfaces fix recommendations. Evaluation results from pre-launch simulation feed into the same dashboards as production traces, maintaining a single connected data loop. A startup program is available for companies under $10M raised and less than five years old.