PRODUCT
BabelFish — The Edge Compiler for LLM Agents
A drop-in edge proxy for LLM agents. Change one URL and BabelFish observes your call patterns, compiles repetitive steps into deterministic code, and runs them locally.
How it works
Three stages. Zero code changes. Your agent keeps running while BabelFish learns and compiles in the background.
Observe
Routes through BabelFish as an edge proxy. Logs structural call patterns — no PII, no payloads. Every LLM invocation is recorded as a typed execution trace with input schemas, output shapes, and latency metadata.
Learn
Clusters repeated call patterns using execution trace analysis. Identifies which calls are deterministic — same input shape always producing the same output. Statistical confidence thresholds prevent premature compilation.
Compile
Generates local code that replaces the LLM call. Tests it against the original with canary traffic. Deploys progressively with automatic rollback on any divergence.
Observe
Routes through BabelFish as an edge proxy. Logs structural call patterns — no PII, no payloads. Every LLM invocation is recorded as a typed execution trace with input schemas, output shapes, and latency metadata.
Learn
Clusters repeated call patterns using execution trace analysis. Identifies which calls are deterministic — same input shape always producing the same output. Statistical confidence thresholds prevent premature compilation.
Compile
Generates local code that replaces the LLM call. Tests it against the original with canary traffic. Deploys progressively with automatic rollback on any divergence.
What compiles?
BabelFish targets the agent steps that are repetitive and deterministic — leaving genuine reasoning to the LLM.
Classification & routing
Intent detection, topic routing, and category assignment. When the same input shapes map to the same labels every time, BabelFish replaces the LLM call with a lightweight local classifier — cutting latency from seconds to single-digit milliseconds.
Structured extraction
Name, address, date, amount — parsed from known formats. BabelFish learns the extraction schema from repeated traces and compiles it into regex-based or parser-based code that handles every variation the LLM saw, without the token cost.
Guardrail checks
PII detection, toxicity filters, and format validation. These safety checks follow deterministic rules that an LLM re-derives identically every time. Compiled guardrails run in microseconds with zero hallucination risk.
Format transformation
JSON ↔ XML, markdown → HTML, schema migration. Structural transforms that follow fixed mapping rules are perfect compilation targets. BabelFish generates transformation code that handles every edge case the LLM encountered during observation.
Retrieval re-ranking
Static relevance scoring that doesn’t change per query. When retrieval results follow stable scoring patterns, BabelFish compiles a lightweight ranker that applies the same logic without an LLM round-trip — keeping RAG pipelines fast and cheap.
Prompt chains
Multi-step prompts with fixed templates and variable slots. When a chain always follows the same path given the same input type, BabelFish collapses the entire sequence into a single compiled function — eliminating multiple LLM round-trips.
Every compiled path is tested before it runs.
BabelFish doesn’t just compile — it validates. Canary testing, automatic rollback, and continuous drift detection ensure compiled paths stay accurate over time.
Canary testing
Before any compiled path goes live, BabelFish routes 5% of real traffic through both the compiled code and the original LLM call simultaneously. Outputs are compared token-for-token.
Traffic ramps progressively with automatic halt at any stage if divergence exceeds configurable thresholds.
Drift detection
Real-world input distributions change. BabelFish continuously monitors compiled paths by sampling production traffic and comparing compiled outputs against the LLM baseline.
When input patterns drift beyond the observed training distribution, the compiled path is automatically flagged and traffic is rerouted back to the LLM until re-compilation completes.
One-click rollback
Any compiled path can revert to the original LLM call in under 1 second. Rollback is atomic — no partial states, no downtime.
Automatic rollback triggers on canary failure, drift alerts, or error-rate spikes. Manual rollback is always available from the Nexus dashboard or the CLI.
Deploy your way.
BabelFish runs wherever your agents run. Choose the deployment model that matches your compliance and performance requirements.
Hosted Cloud
Fastest start. Managed infrastructure, zero ops overhead. Data processed in-region with SOC 2 Type II compliance.
VPC
Runs inside your cloud account. Your network, your rules, our updates. Supports AWS, GCP, and Azure with Terraform modules.
On-Prem
Air-gapped deployment for regulated industries. Full data sovereignty with no external network dependencies.
Start compiling in 5 minutes.
Change one URL. BabelFish handles the rest — observing, compiling, and deploying deterministic paths. Join the beta and start saving.