Portkey AlternativeWhy Future AGI?Every LLM call.
Controlled from one place.
Gateway and guardrails - unified in a single command center. Sub-100ms PII detection, toxicity blocking, and prompt injection defense at the proxy layer. Unified routing across providers, automatic failover, caching, cost tracking, and full observability. One endpoint to route, guard, and monitor everything.
Future AGI vs Portkey
An honest, capability-by-capability comparison. Where Portkey leads, we say so. Where the difference is in quality of implementation, the row label tells you why.
| Capability | Future AGI | Portkey |
|---|---|---|
| Evaluator Ready-to-use & custom metrics that score your traces automatically. Purpose-built models, not LLM-as-Judge wrappers. | ✓ 70+ purpose-built evaluators & custom evaluator builder powered by Turing models. Future AGI also offers proprietary fine-tuned eval foundation models in three sizes (flash, small, large) for cost ↔ accuracy trade-offs. Hybrid heuristic + LLM scoring. Evals can be fine-tuned on your feedback data. | ✗ No built-in evaluator library. Stores eval scores from external tools (Promptfoo, etc.) and surfaces them in dashboards. Bring your own eval framework — Portkey is the gateway, not the evaluator. |
| Agent simulations Multi-turn testing, adversarial inputs, scripted + agent-generated scenarios at scale. | ✓ Simulate thousands of edge-case conversations before launch. | ✗ No agent simulation engine — gateway and observability only. |
| Agent optimization Close the loop from production traces to improved agent — no manual prompt rewriting. | ✓ agent-opt SDK with GEPA + RL strategies. | ✗ No native optimization layer. |
| Voice-agent observability Full-stack coverage — first-class tracing for VAPI, LiveKit, and Pipecat. | ✓ | ✗ Voice-stack frameworks not natively instrumented. |
| Open-source full platform Self-host the entire stack — observability + eval + guard, not just the gateway. | ✓ Full platform (tracing, evals, guardrails, simulations, optimization, gateway) self-hostable. | Partial Gateway is OSS — but observability, governance, and guardrails UI are SaaS-only. |
| OpenTelemetry-native instrumentation Vendor-neutral tracing — export to Datadog, Grafana, Jaeger, or any OTel backend. | ✓ traceAI is OTel-native from day one. | Partial Custom Portkey SDK with observability data shipped to Portkey's backend; OTel export available but not the primary path. |
| Guardrails AI output gating — block, redact, or rewrite at inference time. | ✓ Native sub-100ms guardrails powered by purpose-trained eval models. Same metrics from dev tests run as production blocking. Included on every plan. | Partial 50–60+ guardrails available, but the high-value ones (hallucination, contextual grounding, advanced moderation) are third-party integrations (Aporia, Patronus, Lakera, Pillar). Native checks are simpler (regex, JSON validity, basic PII). Latency varies by underlying provider. |
| In-platform AI copilot | ✓ Falcon AI — your AI copilot for everything in the platform. | ✗ No in-dashboard copilot. |
| Error tracking Automatically surface, group, and triage agent failures. | ✓ Error Feed — Sentry-style error tracking for AI agents. Failures auto-surfaced, grouped, and triaged in one feed. | Partial Logs page tracks gateway-level success/failure, fallback triggers, retries. Solid gateway-layer visibility; no agent-failure grouping or triage at the platform level. |
| Platform independence Roadmap and pricing stability under independent ownership. | ✓ Independent. No parent-company roadmap pressure. | ✗ Acquired by Palo Alto Networks (April 2026). Becoming the AI Gateway inside Prisma AIRS — developer-first focus may shift toward security-platform integration. |
| Agent Playground Build agents inside the platform where you evaluate, observe, and optimize them. | ✓ Drag-and-drop canvas for multi-step agents wired into Tracing, Evaluators, Error Feed, Simulations, Guardrails, and Optimizer. | ✗ No agent builder. |
| Built-in AI Command Center (Gateway) Model routing, fallback, and caching at the platform layer. | ✓ Built-in gateway as part of the platform. | ✓ Flagship product. 1,600+ LLMs, <1ms latency, mature fallbacks / load balancing / caching / retries — Portkey's strongest area. |
| Prompt management & versioning Prompt registry with version history and deployment workflows. | ✓ | ✓ |
| Pricing model How you pay as you scale. |
Free forever — unlimited users, all products. HIPAA, SAML SSO, SCIM included on Enterprise. |
Dev tier: 10K logs / 30-day retention. Pro is usage-based on logs (~$36 for 500K req · $81 for 1M · $171 for 2M, plus base fee). Logs only — LLM token costs are separate. |
Comparison reflects publicly available information as of 2026. Spotted something wrong? Tell us and we'll correct it.
The only gateway with
native guardrails built in
Most gateways treat guardrails as a third-party integration that adds latency. Our guardrails are built into the gateway itself - PII detection, toxicity blocking, hallucination checks, prompt injection defense, topic enforcement - all executing inline at sub-100ms. No external API calls. No extra hop. The gateway is the guardrail.
See guardrail policiesOne OpenAI-compatible endpoint routes to GPT-4o, Claude, Gemini, Llama, Mistral, or any model. Automatic failover when providers go down. Load-balance across API keys to avoid rate limits. Your application code never changes - the gateway handles provider switching transparently.
See supported providersEvery request flowing through the gateway is automatically logged with full traces - input, output, latency, tokens, cost, guardrail decisions. Attach evaluation metrics to score quality in real-time. No separate observability integration needed - the gateway is the telemetry layer.
Explore tracingReal-time cost tracking per model, per team, per project. Set spend caps and budget alerts before the bill surprises you. Rate limit by user, team, or API key. Cache identical and semantically similar responses to cut costs on repetitive queries - up to 95% savings on stable workloads.
View cost analytics Govern every LLM call
from one proxy
Block PII and toxic output inline
Every LLM response is scanned for PII, toxic content, and policy violations before it reaches the user. Sub-100ms enforcement. No changes to your application code - the gateway intercepts and blocks at the proxy layer.
Failover across providers automatically
When OpenAI goes down, the gateway routes to Claude or Gemini automatically. No code changes. Configure primary and fallback providers with priority, latency, or cost-based routing rules.
Cap spend before the bill arrives
Set per-team, per-project, and per-model budgets. Get alerts at 80% usage. Hard-cap at 100% so no runaway query burns through your credits overnight. Real-time cost dashboards, not end-of-month surprises.
Defend against prompt injection
The gateway scans inputs for prompt injection patterns before they reach the LLM. Jailbreak attempts, system prompt extraction, and instruction override attacks are blocked at the perimeter - your agent never sees them.
Audit every LLM interaction
Every request and response is logged with full metadata - user, team, model, tokens, cost, latency, guardrail decisions. Export logs for SOC 2, HIPAA, or internal compliance. Prove your AI is governed.
Cache and cut costs on stable queries
Identical prompts hit the cache instead of the LLM. Semantic caching catches near-identical queries too. Customer support, FAQ bots, and documentation agents see up to 95% cost reduction on repetitive traffic.
From open endpoint to
governed gateway in three steps
Point your app at the gateway
Swap your LLM provider URL for the gateway endpoint. OpenAI-compatible API - your existing SDK code works unchanged. Configure providers, fallback order, and rate limits in the dashboard.
Define guardrail policies
Set input and output guardrails - PII blocking, toxicity filtering, topic enforcement, prompt injection defense, hallucination checks. Choose enforcement mode per rule: log, flag, or block. Policies apply to all traffic flowing through the gateway.
Monitor cost, quality, and safety
Every request is traced with cost, latency, tokens, guardrail decisions, and evaluation scores. Real-time dashboards show spend per team, block rates per rule, and model performance. Alert on anomalies.
Powering teams from
prototype to production
From ambitious startups to global enterprises, teams trust Future AGI to ship AI agents confidently.