Feature-flag tools weren't built for changes that measure themselves
Building got cheap. Knowing what each change did didn't. Traffical is the control plane where velocity, containment, and evidence keep pace with each other.
The bottleneck moved
If you ship ten changes a week and evaluate two, the other eight are guesses.
A change that used to take a sprint now takes an afternoon, and agentic tools keep pushing that cost down. What didn't get cheap is knowing what each change did — what to keep, what to revert, what to double down on.
Traffical is built on the premise that three things have to keep pace with each other. Most tools accelerate the first and leave the other two as manual follow-up.
How fast you ship
User-facing changes, in production.
How fast you contain
Detect and stop the ones that hurt.
How fast you produce evidence
Numbers you'd defend in a review.
The problem with the current stack
Every option comes with a tradeoff you shouldn't have to accept.
Flag-shaped thinking
Booleans are a ceiling. Real products tune prices, ranking weights, prompts, and thresholds. Every new variation means a new flag and more branching.
Measurement bolted on
A second event pipeline to keep in sync, and outcomes your SDK never sees — renewals, refunds, tickets — simply don’t count.
Governance as a process
A checklist in a doc, a launch review on Thursdays. Nothing in the tool stops an unmeasured change from carrying traffic — least of all one an agent opened.
Traffical's approach
Four decisions that make the safe path the default path.
Parameters, not flags
A typed, versioned value with a default. Tests, rollouts, flags, and bandits are all policies over the same primitive.
Local resolution
Your SDK resolves in-process from a cached bundle. Sub-millisecond, works at the edge, survives us being unreachable.
Warehouse-native
Metrics as SQL against the warehouse you already trust. Same statistics, no second pipeline, outcomes SDKs never see.
Governance in the product
No traffic without an approved measurement plan. Risk computed from surfaces. Every transition writes a decision record — the layer that makes handing work to agents affordable.
How Traffical compares
A side-by-side of the options teams weigh for shipping measured change.
| Capability | Traffical | Feature-flag tools | A/B platforms | Warehouse-only | DIY config |
|---|---|---|---|---|---|
| Unit of control | Typed parameter | Boolean flag | Experiment | — | Env var |
| Non-boolean values | Native | Workarounds | Variant payloads | ✕ | Manual |
| Resolution latency | Sub-ms, local | Local | Network call | n/a | Local |
| Concurrent isolation | Layers, orthogonal | Manual | Mutex groups | ✕ | ✕ |
| Measurement source | Warehouse + native | ✕ | Own pipeline | Warehouse | ✕ |
| Sequential testing & CUPED | Built in | ✕ | Sometimes | You implement | ✕ |
| Traffic gated on a plan | Enforced | ✕ | ✕ | ✕ | ✕ |
| Risk class & approvals | Computed per change | Basic roles | Basic roles | ✕ | ✕ |
| Decision audit trail | Every transition | Flag history | Partial | ✕ | Git log |
| Agent autonomy model | MCP, risk-gated | ✕ | ✕ | ✕ | ✕ |
| Adaptive optimization | Thompson, UCB1, contextual | ✕ | Sometimes | ✕ | ✕ |
| Best for | Measured change at speed | Release toggles | Classic A/B | Retro analysis | Small teams |
Who it's for
Teams that want the velocity increase without losing the ability to answer "did it work?"
Wants more shots on goal, defensibly
Ten changes a week instead of two, each with a measurement plan attached before it carries traffic — so the roadmap review argues about strategy, not about whether the numbers are real.
→ start with the change model
Wants one source of truth, not two
Metrics defined as SQL on the warehouse that's already the system of record. Certified definitions, sequential testing, CUPED — statistics the data team would have written themselves.
→ start with how it works
Wants agent velocity without incidents
Fleets of coding agents shipping change, inside guardrails that pause on breach and a revert path that works. Config as code, typed SDKs, CI drift checks.
→ start with how it works
Who it's not for
Traffical does one thing well. These jobs belong to other tools.
Product analytics
If you want funnels, session replay, and exploratory event dashboards, keep your analytics suite. Traffical is focused on operating and measuring changes — it reads your analytics, it does not replace them.
Release toggles only
If all you need is turning code paths on and off with no measurement or governance, a feature-flag tool is cheaper and simpler.
Infra monitoring
Traffical watches guardrail metrics on changes. It is not your APM, log search, or on-call paging system.
Four numbers that say the platform is infrastructure, not a habit
If these don't move year over year, you're going faster without getting more confident.
How a storefront team ships 40 changes a quarter
Same headcount as the year before. Zero measurement incidents.
Acme Storefront
A mid-market commerce team running checkout, pricing, ranking, and CRM changes across four surfaces — with three coding agents opening most of them.
Agents declare the parameter, scaffold the change, and propose a plan. The measurement plan resolves from two certified protocols, so low-risk frontend work starts without ceremony. Pricing changes wait for a person — by design. Two guardrail breaches paused themselves overnight and were reverted before the morning.
Ship faster than last year. Be more certain than last year.
Both, or it isn't infrastructure. Start with one parameter and one certified metric.