High-performance optimization,
handled end to end

Move faster · reduce friction · make better decisions

Sematryx formulates the problem, selects the right optimization strategy, solves it, and explains the result.

Turns natural language into math · Maps the solution landscape · Learns which strategies work · Benchmark-backed performance

Works with

Claude Desktop
Cline
Python SDK
REST API

Sematryx does not rely on a single fixed optimizer. It analyzes the problem, selects and tunes the right strategy, and explains the result.

Use Sematryx through conversation, MCP, or API. It formulates and analyzes problems, selects and tunes the right strategy, and returns explainable results.

Conversational

Describe problems in plain English when you want a guided formulation

MCP for agents

Tool calls map to the same engine as the API and SDKs

Engine routing

Portfolio of solvers and policies—not one fixed algorithm

Optional learning

Transfer and warm-start when your policy allows it

Explainable

Configurable depth for stakeholders and compliance

REST API & SDK

Integrate optimization into any workflow

Performance

A high-performance optimization engine

MCP and conversational flows are how you access Sematryx today—the credibility of the product is the engine: benchmarked behavior, multi-solver orchestration, and explainable outcomes for serious problems.

See performance data

Benchmarked results

Head-to-head results on standard test functions and realistic problem shapes—not just demos.

Multi-solver portfolio

Strategy selection draws from a portfolio of solvers so the engine matches the problem, not a single default.

Adaptive selection & transfer

Warm starts and learning from prior runs can reduce evaluations as your workload repeats.

Reliability under constraints

Built for constraint-heavy decision problems where black-box tools often fail or stall.

Landscape-aware behavior

Topology and landscape signals inform how aggressively to search—without turning the product into an architecture diagram.

Summary metrics on the Performance page are illustrative of benchmark scenarios—see full tables and methodology there.

NewPatent Pending

Formulate in plain English—same engine underneath

Natural language helps you specify objectives and constraints; Sematryx still solves with the hosted optimization engine and returns numbers plus explanations your team or agents can use.

Zero technical barrier—works for anyone with an optimization problem
AI agent asks clarifying questions and validates inputs in real-time
Steers you toward well-posed formulations the engine can execute reliably
Perfect for marketing managers, operations teams, and domain experts
Conversational Optimization
U
You
"I want to optimize my marketing budget across Google, Facebook, and LinkedIn to maximize ROI"
AI Agent
"I understand you want to optimize your marketing budget. What is your total marketing budget?"
U
You
"$50,000"
Optimization Complete
Optimal Allocation:
Google: $28,500 (57%)
Facebook: $15,000 (30%)
LinkedIn: $6,500 (13%)
Total ROI: 242% • Expected Revenue: $171,000
No code needed

Use cases

Problem classes the engine handles well

Examples—not a catalog of vertical suites. Agents often call Sematryx when a workflow hits a continuous or combinatorial optimization problem; the same engine backs direct API use.

ML / Training

Hyperparameter Tuning

AI agents use Sematryx to find optimal learning rates, batch sizes, and regularization — without hand-coding grid search or random sampling.

lr=0.00312, dropout=0.18 → 2.3% better validation accuracy
Finance / Operations

Resource Allocation

AI agents use Sematryx to distribute budgets, staff, inventory, or compute across competing objectives with hard constraints.

Budget allocation across 8 channels → 23% higher ROI within cap
Ops / Logistics

Scheduling & Routing

AI agents use Sematryx to build conflict-free schedules and minimize routing cost across multi-variable constraint systems.

Staff schedule across 40 shifts → 18% fewer overtime hours
Infrastructure

Model & System Configuration

AI agents use Sematryx to tune infrastructure configs, model serving parameters, and pipeline settings for throughput or cost.

Replica count + batch size → 40% cost reduction at same latency

Full use-case buckets (resource allocation, portfolios, scheduling, compliance-heavy decisions) →

AI-Native

MCP plugs agents into the engine

Agents call the same optimization service as your SDK and REST workflows: structured problems in, optimal points and objective values out—plus explanations the agent can quote or summarize for users.

  • Claude, GPT, Cursor, and other MCP clients invoke Sematryx as a tool
  • Responses pair numeric results with rationale suited for downstream reasoning
  • Heavy optimization runs on hosted infrastructure, not in the agent loop
Learn about MCP integration →
MCPAgent → Sematryx → Response
Agent Request
"Optimize portfolio for 8% return, max 30% single position"
Sematryx Response
allocation: [0.35, 0.28, 0.22, 0.15]
"Balanced risk-adjusted return while satisfying the 30% max position constraint..."
Agent to User
"I've optimized your portfolio. Here's the recommended allocation and why..."

Product workflow

Formulate, solve, explain

The same engine backs APIs, SDKs, and MCP—positioned around outcomes, not internal architecture labels.

Formulate

Turn objectives, bounds, and constraints into a problem the engine can run—via SDK, REST, or guided conversational flows.

Solve

Adaptive strategy selection and a multi-solver portfolio target strong solutions on hard landscapes, with transfer from prior runs when your workload repeats.

Explain

Receive decision-relevant explanations and audit-friendly narrative—not just an optimum vector—so teams can trust and defend results.

One API Call

Define your problem, set constraints, get an optimized solution. No infrastructure to manage.

Full Explainability

Every decision documented and traceable for audits and regulatory compliance.

Built for real constraints

Hard limits, business rules, and audit expectations—explainable outputs for teams that have to justify decisions.

Gets Smarter

Continuous learning means better results over time, automatically.

Natural Language Interface

Describe problems in plain English. No code or optimization expertise required. Patent pending.

Early access opening soon

Join the waitlist for the hosted optimization engine—API, MCP, and conversational access

Join Waitlist →

Simple, Pay-Per-Solve Pricing

Metered by solve complexity. Start free with 100 solves/month—same engine whether you call it from code, MCP, or conversational flows.

Free

$0forever

Get started with optimization basics

  • 100 solves/month
  • Public learning pool
  • Community support
  • No credit card required
Join Waitlist
Most Popular

Pay-as-you-go

$0.01– $0.05/solve

Pay only for what you use

  • Unlimited solves
  • Price scales with complexity
  • Private Learning Store
  • Priority support
  • Credit packs save ~50%
Buy Credits

Enterprise

Custom

For large organizations

  • Volume discounts
  • Dedicated support & SLA
  • SSO & audit logs
  • Custom integrations
Contact Sales

Cost Per Solve

ComplexityDimensionsMax EvaluationsCost
Small≤ 10≤ 1,000$0.01
Medium≤ 50≤ 5,000$0.03
Large≤ 100≤ 10,000$0.05

Save ~50% with Credit Packs

5,000 solves for $75 (just $0.015/solve). Prepaid credits never expire.

Buy Credit Pack

Questions? Check out our pricing FAQ or contact us.

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