Phantm. | Prompt Optimization Gateway

AI Token spend is now every CFO’s growing charter.

Multi-step appdev pipelines multiply calls per request.
Token waste hides inside prompts, RAG, and bloated outputs.
Enterprise clients need transparent FinOps & strict audit trials.

Phantm sits in the request path optimizing every call.

Streaming compatible
Base URL Swap
Tool/function calling passthrough

Optimization is a pipeline, not a mystery.

API Call

Cache

Gate

Compress

Route

Return

Real Time execution

Seeing your LLM bill spike?

Phantm is a drop-in replacement for your LLM API calls that reduces token usage in real time while maintaining response quality. No workflow changes required.

No black-box behavior. Full guardrails. Production-safe optimization for agentic systems.

If you're running agent workflows and watching token spend climb, Phantm keeps costs under control without degrading outputs.

Coming soon

Quality-safe compression + pruning.

Remove low-value context without changing meaning.
Measurable token delta + clear edit trail.
Prompt alterations + savings trace.

Route by difficulty; fallback when uncertain.

"We optimize use of Enterprise approved models to minimize cost while maintaining outcome quality and integrity."

Eliminate repeated spend.

"Reset password?"

"Forgot password?"

"Password help?"

Semantic Match Similarity Threshold > 0.99

Zero-Cost Response

Budgets + policies per tenant, enforced in the hot path.

Approved
models

Budget
caps

Rate
limits

Policy
Opt-in/out

Every change is explainable, measurable, reversible.

Explainable. Logs + diffs for every decision.
Measurable. Token/cost deltas per endpoint.
Reversible. Gradual rollout + instant rollback.
Valuable. We charge a % of verified savings: we ONLY win if you win.

Others report spend. We reduce it with proof.

Eval-gated + reversible Unproven / manual Reports spend Reduces spend

Kong AI Gateway

Langfuse

Keywords AI

Portkey

Prompts.ai

Phantm

Meet the team.

Rohan

Suri

B.S Chem + Math Yale '28

Owns pilots: outreach, qualification, closing
Runs product testing + customer proof artifacts
Research experience in NN fine-tuning + simulations; helped secure ~$2M Lily grant

Thomas

Papavramidis

B.S CS + Math Yale '28

Architect: leads product and system development
Experience building predictive systems
International Math + Physics Olympian

Aadi

Gujral

B.S CS + Econ Yale '28

GTM: leads BD + partnerships, branding
Created app w/7k+ users; led conservation project featured in NYT
IB/PE background; built AI agents expanding outreach 3-5x