ARTF v1.0 - IAB Tech Lab's Containerisation Framework That Promises to Cut RTB Latency by 80%
Verified facts: Released for public comment 13 November 2025 · Comment period: until 15 January 2026 · Steward: IAB Tech Lab · Go reference implementation by Index Exchange (AGPL-3.0) · Spec: Creative Commons Attribution 3.0 · Supports MCP and A2A as agent communication layers · Contributors include The Trade Desk (Arpad Miklos), Chalice (Adam Heimlich), Index Exchange (Joshua Prismon) · Part of AAMP initiative · Target: RTB round-trip from 600–800ms to ~100ms (-80%)
What ARTF Is
ARTF is a containerisation architecture for programmatic advertising. It allows technologies - DSPs, SSPs, enrichment partners, measurement solutions, AI agents - to operate within the same virtual environment rather than communicating across separate networks via API calls. The result: auction-speed agentic decisioning that was previously impossible within RTB latency constraints.
ARTF is explicitly different from AdCP. AdCP defines how agents communicate in the planning and buying layer above the auction. ARTF defines how agents participate in real-time bidding execution at the infrastructure level, within the auction. IAB Tech Lab describes them as complementary rather than competing.
How Containerisation Works
ARTF packages agent or technology code into a software container that runs inside a partner's infrastructure. A DSP's bidding logic, a fraud detection agent, and a viewability measurement service can all operate in the same virtual machine - communicating at memory speed rather than network speed. This eliminates the network hops that create the 600–800ms round-trip time of current OpenRTB implementations.
The gRPC service definition: RTBExtensionPoint.GetMutations(RTBRequest) - an agent receives a bid request, proposes mutations (segment activations, deal adjustments, bid shading, viewability additions), and returns them within the latency budget. A working Go reference implementation is publicly available on IAB Tech Lab's GitHub.
🎯 Primary use cases
- Real-time audience segment activation within the bid window
- Dynamic deal management - activate, suppress, adjust per impression
- Intelligent bid shading with in-auction price optimisation
- Real-time viewability and brand safety scoring before bid response
- Fraud detection at auction speed - not post-bid
✓ Upsides
- 80% latency reduction - opens new in-auction possibilities
- Builds on OpenRTB - lowest adoption friction
- Go reference implementation available now
- Fraud detection moves to real-time
- IAB Tech Lab governance - highest trust in industry
- Reduces compute and energy cost vs server-to-server
✗ Downsides
- Still in public comment - not finalised as of March 2026
- Requires both buyer and seller in same containerised environment
- Infrastructure migration cost for distributed architectures
- Security surface of shared containers needs careful design
- Only 14 companies in Working Group at v1.0 launch