Demo
Train custom AI agents from your data.
Upload your knowledge, define behavior, and deploy a production-ready AI agent with evals, API, and MCP endpoints in one control plane.
01 · Upload
Raw domain files
How it works
Seven stages from raw data to deployed specialist
Ingest domain data
Parse, chunk, and index your uploaded files
Build dataset
Generate structured training examples from content
Generate evals
Create quality rubrics and test suites
Recommend strategy
Choose the best optimization path
Optimize specialist
Build the specialist artifact
Benchmark quality
Measure answer quality and latency
Deploy and serve
Publish live API and MCP endpoints
Healthcare Policy Specialist
Grounded in 47 policy documents
What are the updated pre-authorization requirements for outpatient cardiac rehabilitation under the 2024 CMS guidelines?
Under the 2024 CMS Final Rule (CMS-1787-F), outpatient cardiac rehabilitation programs now require prior authorization only for sessions exceeding the initial 36-session block. Key changes:
- Elimination of prior auth for Phase I cardiac rehab referrals from qualified providers
- New 72-hour expedited review pathway for post-acute patients
- Updated documentation requirements per CMS Transmittal 12441
Why Speco
The missing layer between foundation models and production
Foundation models are powerful but generic. Speco gives you the control plane to make them exceptional at your domain.
Training abstraction
Define your specialist, upload data, and Speco handles the rest. No infrastructure to manage.
Dataset control
Structured, versioned, inspectable training data. Every example traceable to its source.
Eval-first workflow
Quality is measured before deployment. Auto-generated eval suites ensure domain requirements are met.
Strategy recommendation
Speco analyzes your data and recommends whether prompt engineering, RAG, or fine-tuning is the right path.
Deployment-ready
One click from optimized model to live endpoint. API keys, usage tracking, and health monitoring included.
MCP-native
Deployed specialists are automatically available as MCP tools for downstream AI agents.
Product
Everything you need in one control plane
Specialist
Healthcare Policy Advisor
Pipeline Run
Full Pipeline — Run #47
Deployment
healthcare-policy-v3
Endpoint
specoai.com/api/infer?endpoint=healthcare-policy
API Key
sk-speco-****...****7f3a
Requests
12.4k
Avg latency
340ms
Success
99.8%
MCP Integration
Agent-ready specialist
{ "tools": [ { "name": "query_policy" "description": "Query healthcare policy" } ] }
Benchmarking
Measurable, not magical
Every specialist is benchmarked before deployment. Pass rates, mean scores, latency, and per-case breakdowns give you confidence that quality is real.
Benchmark Summary
passingEval cases
142
Mean score
0.87
P95 latency
480ms
{ "mcpServers": { "speco-healthcare": { "url": "https://specoai.com/mcp/healthcare-policy" "transport": "streamable-http" } } }
query_specialist
Query with domain questions
specialist://status
Deployment health and benchmarks
analyze_with_specialist
Structured analysis template
MCP Integration
Your specialists are agent‑ready
Every deployed specialist is automatically exposed through the Model Context Protocol. Downstream AI agents can discover and use your specialists as tools, resources, and prompts.
Pricing
Simple, predictable pricing
Start free. Scale when you need to.
Pricing localizes automatically for Brazil, the United States, Canada, and Europe.
Free
Explore the platform. Build your first AI agent.
Builder
For solo creators and indie builders shipping AI agents in production.
Localized checkout pricing
Growth
For startups and small teams up to 5 members building production AI agent systems.
Localized checkout pricing
Enterprise
For teams scaling production AI with dedicated resources and compliance.
Localized checkout pricing
Larger enterprise? Contact Speco Team
Build specialized agents from your own data.
From raw files to deployable AI systems in one control plane.