OUR SERVICES

//  Define an AI Agent with custom tools
"code-keyword">import { Agent } "code-keyword">from '@trailblaze/ai-sdk';

"code-keyword">const researchAgent = "code-keyword">new Agent({
model: 'gpt-4o',
systemPrompt: 'You are a research assistant that helps find information.',
tools: [searchTool, summarizeTool, databaseTool]
});

//  Create a customer service agent with memory
"code-keyword">const customerAgent = "code-keyword">new Agent({
model: 'claude-"code-number">3-opus',
memory: "code-builtin">true,
systemPrompt: 'You are a helpful customer service agent.',
tools: [
  orderLookupTool,
  productCatalogTool,
  ticketCreationTool
]
});

//  Deploy an agent with multi-step reasoning
"code-keyword">await agent.execute({
task: "Research market trends ">for AI in healthcare",
reasoning: "step-by-step",
outputFormat: "markdown",
maxSteps: "code-number">5,
verbose: "code-builtin">true
});

//  Connect agent to your business systems
"code-keyword">const salesAgent = "code-keyword">new Agent({
model: 'gpt-4o',
integrations: {
  crm: crmConnector,
  email: emailConnector,
  calendar: calendarConnector
},
tools: customBusinessTools
});

//  Define MCP context "code-keyword">for standardized AI interactions
"code-keyword">import { MCPContext } "code-keyword">from '@trailblaze/mcp';

"code-keyword">const context = "code-keyword">new MCPContext({
metadata: {
  version: '"code-number">1."code-number">0',
  provider: 'Trailblaze Labs',
  model: 'gpt-4o',
  purpose: 'Customer support automation'
},
permissions: ['read:customer-data', 'create:tickets'],
constraints: {
  maxTokens: "code-number">2000,
  temperatureRange: ["code-number">0."code-number">1, "code-number">0."code-number">7],
  contentFiltering: 'moderate'
}
});

//  Implement MCP "code-keyword">for transparent AI operations
"code-keyword">const response = "code-keyword">await mcpClient.execute({
context: context,
input: userQuery,
tracing: "code-builtin">true,
auditLog: {
  enabled: "code-builtin">true,
  retention: '90d',
  detailLevel: 'comprehensive'
},
fallbacks: [
  { condition: 'timeout', action: 'retry', maxAttempts: "code-number">3 },
  { condition: 'error', action: 'human-escalation' }
]
});

//  MCP "code-keyword">for multi-model orchestration
"code-keyword">const workflow = "code-keyword">new MCPWorkflow({
steps: [
  {
    id: 'understand',
    model: 'text-understanding',
    output: 'query_intent'
  },
  {
    id: 'research',
    model: 'knowledge-retrieval',
    input: '{{steps.understand.output}}',
    output: 'relevant_data'
  },
  {
    id: 'generate',
    model: 'content-generation',
    input: {
      intent: '{{steps.understand.output}}',
      data: '{{steps.research.output}}'
    }
  }
],
observability: {
  metrics: ['latency', 'token_usage', 'error_rate'],
  logging: 'detailed'
}
});

//  MCP "code-keyword">for regulatory compliance
"code-keyword">const compliantResponse = "code-keyword">await mcpProcessor.process({
input: userRequest,
context: context,
compliance: {
  regulations: ['GDPR', 'HIPAA', 'CCPA'],
  piiHandling: 'redact',
  dataResidency: 'EU',
  auditTrail: "code-builtin">true
},
explainability: {
  level: 'detailed',
  format: 'human-readable',
  includeConfidenceScores: "code-builtin">true
}
});