PydanticAI gives you a clean, type-safe way to write agents in Python; it does not give you the system that runs them. With a framework you assemble the parts and operate the result — availability, durable state, governance, and the pager are yours. With a platform the system comes assembled and operated, under a contractual SLA.
PydanticAI is a typed Python agent library from the team behind Pydantic. It gives you model-agnostic agents, structured and validated outputs, dependency injection, MCP support, and graph-based workflows, all checked by your type checker. Those are components for writing agents, not a running system, so your engineers wire in the durability, streaming, and governance around them.
Then your team runs it — scaling it, handling failover and recovery, and carrying the pager. The framework publishes no application-level SLA, so the availability of the running system is yours to guarantee.
Akka gives you the agents, durable state, streaming, APIs, and governance as one pre-integrated runtime. You describe the system you want, and the platform generates it, tests it, and runs it. Because everything runs in one runtime, a system that compiles is ready for production.
Akka keeps it running around the clock, with active-active replication and automatic failover, and stands behind a contractual 99.9999% availability SLA on the running system.
| Dimension | With PydanticAI | With Akka |
|---|---|---|
| Availability | The framework publishes no availability SLA, because it does not run anything — uptime and recovery belong to the infrastructure your team assembles. A contractual SLA is offered only on the Logfire Enterprise observability service, not on your agents. | Akka owns 99.9999% on the running system — a ~31-second yearly budget — active-active, sub-1-minute RTO, zero-byte RPO. |
| State & memory | Agent state lives in process memory; durability is delegated to an external engine — Temporal, DBOS, Prefect, or Restate — that checkpoints or replays it in its own datastore, which you provision, scale, and keep available. | Held in memory, active-active replicated — 4 ms reads, sub-10 ms writes. Durability is a runtime property, not a database round-trip. |
| Governance | Through Logfire, calls are traced and scored after execution. Inline blocking, hash-chained evidence, human override, and pre-deployment classification are the customer's to build. | Risk teams define policies independently; the runtime enforces them on every action — HITL, HOTL, guardrails, evaluations — with no developer code, into tamper-evident storage. |
| Runtime track record | PydanticAI reached its first major version in September 2025, with the current stable release in June 2026 and V2 in beta; it delegates the durable runtime to external engines rather than running one itself. | since 2007, 100,000+ deployments — the runtime behind systems two billion people use daily. |
| Infrastructure cost | The Python infrastructure footprint, plus the separate datastore and operations of the durable-execution engine, plus the memory, streaming, API, observability, and governance tiers — each provisioned and operated separately. | One shared-compute runtime carries the same volume on up to 90% less infrastructure, at a fixed annual fee. Akka Optimize keeps improving the models on your own production traffic, so cost per task keeps falling as the system runs. |
| Portability | A production deployment accretes dependencies on the hosted Logfire observability service and on whichever durable-execution engine and datastore provide recovery. | Any cloud, on-prem, or sovereign — portable specs, BSL licensing, no per-trace meter. |
It comes down to who writes the policy and when it acts. With PydanticAI, governance is observability through Logfire, applied to logs after execution. With Akka, risk and compliance write the policies independently of the agents, and the runtime enforces them on every action — with no developer code to customize.
Trace & evaluate
PydanticAI's governance story is Pydantic Logfire, the team's commercial observability product. It traces agent calls and runs evaluations for quality and monitoring, with SOC 2 Type II, HIPAA, and GDPR for the observability service and an EU data region. It works on the record of what already ran.
Because it observes and evaluates logs, the actual inline blocking, the hash-chained immutable evidence, the human override on a running process, and the classification of a system before it ships are things you assemble and bolt on yourself, project by project. Evaluation is a job you run against datasets, not something gating production.
Block & escalate
With Akka, your risk and compliance teams write the policies themselves, in a separate versioned lifecycle that is independent of the agents — there is no developer code to customize. The runtime enforces every policy inline at the agent boundary, so human-in-the-loop approvals, human-on-the-loop halt switches, sanitizers, guardrails, evaluations, testing gates, and simulations all run before an action executes and block or escalate anything that does not pass.
Every call is traced automatically into petabyte-scale, tamper-evident storage, and that same trace data feeds continuous evaluations that keep running in production, right alongside your agents.
Reach for the framework when you are building agents in Python and want your type checker and IDE to catch errors at write-time, when the system is internal or low-stakes enough that some downtime is fine, and when your team is ready to own the durability, scaling, recovery, and governance that come with running it yourself. It is also the right call when you want low-level control over every component.
Reach for the platform when the system has to stay up, survive failure, and recover on its own, and when it has to pass an audit and enforce governance while it runs. It fits when you want a single vendor accountable for availability under an SLA, and when you would rather ship the system than build and operate the plumbing underneath it.
A sample of agentic and real-time systems on Akka Platform:
Akka Platform builds, runs, and governs agentic systems under a contractual SLA. Tell us what you are building, and we will show you how it runs in production.
