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  <url>
    <loc>https://www.mmanalytics.tech/services</loc>
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    <priority>1.0</priority>
    <lastmod>2026-02-11</lastmod>
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      <image:title>Services</image:title>
    </image:image>
    <image:image>
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      <image:title>Services</image:title>
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    <image:image>
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      <image:title>Services - LLM &amp; Intelligent Workflow Architecture</image:title>
      <image:caption>I engineer production-ready LLM systems that operate as structured, reliable components within larger software architectures. My work includes multi-agent workflows where specialized agents handle task decomposition, retrieval, tool invocation, validation, and response synthesis under controlled execution paths. I build retrieval-augmented generation (RAG) systems using embedding generation pipelines, cosine similarity search, and top-N retrieval strategies over vector databases (e.g., pgvector) to ground outputs in client-specific data. Where domain adaptation is required, I implement parameter-efficient fine-tuning approaches such as LoRA and QLoRA, and manage model versions through controlled deployment patterns and registry-backed workflows. I work with managed model platforms such as AWS Bedrock to integrate foundation models into enterprise environments with governance, access control, and auditing requirements. Systems are deployed within scalable microservice architectures with defined latency thresholds, structured observability, and release criteria suitable for production use. Deterministic guardrails, tool-based computation, and LLM tracing frameworks are incorporated to ensure correctness, traceability, and measurable performance under real-world constraints. Representative Work - Architected and productionized multi-agent LLM workflows for analytics generation and validation, combining structured tool calls, deterministic checks, and retrieval grounding to eliminate hallucinations in accuracy-critical outputs. - Built RAG systems over enterprise transcript and engagement datasets using embedding pipelines, cosine similarity search, and vector database indexing to enable semantic search and contextual Q&amp;A. - Integrated LLM-driven services into containerized backend applications using LangChain-based orchestration patterns, AWS Bedrock-managed models, and Langfuse observability for tracing, evaluation, and performance monitoring. Core Technologies Multi-agent orchestration; LangChain-based workflow design; retrieval-augmented generation (RAG); embedding generation pipelines; cosine similarity and top-N retrieval methods; vector databases (pgvector); parameter-efficient fine-tuning (LoRA, QLoRA); model versioning and registry-backed deployment; AWS Bedrock-managed foundation models; prompt engineering and structured prompting; tool-based LLM execution; deterministic validation layers; API-based model serving; latency-aware deployment patterns; LLM observability and tracing (Langfuse); scalable microservice integration; evaluation frameworks for generative systems.</image:caption>
    </image:image>
    <image:image>
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      <image:title>Services - AI Strategy &amp; Technical Roadmapping</image:title>
      <image:caption>I help organizations translate business objectives into implementable AI systems with clear architectural boundaries and phased execution plans. My work includes defining data requirements, evaluating feasibility under existing infrastructure constraints, and identifying where statistical ML, LLM systems, or deterministic logic are most appropriate. I structure initiatives to balance time-to-value with long-term maintainability, incorporating cost modeling, latency considerations, and governance requirements early in the design process. Roadmaps include dependency sequencing, risk identification, and production-readiness criteria to prevent stalled prototypes. Where needed, I guide build-versus-buy decisions and managed model integration strategies. The result is a technically grounded plan that aligns product ambition with operational reality. Representative Work - Developed a multi-year AI and data roadmap for an e-commerce portfolio firm, outlining phased implementation of analytics and predictive systems based on existing data maturity and infrastructure constraints. - Defined architecture and execution plans for enterprise analytics platforms, sequencing ingestion, modeling, and deployment milestones to reduce delivery risk. - Advised stakeholders on LLM integration strategies, evaluating feasibility, governance implications, and infrastructure readiness prior to production deployment. Core Technologies AI architecture planning; data maturity assessment; build-versus-buy analysis; phased implementation strategies; cost and latency modeling; governance integration; dependency sequencing; risk assessment frameworks; production-readiness criteria; foundation model integration strategy.</image:caption>
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  </url>
  <url>
    <loc>https://www.mmanalytics.tech/blog-forte</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2025-05-08</lastmod>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/blog-forte/2016/2/22/alveolar-glottis-t5g94</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2016-02-22</lastmod>
    <image:image>
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      <image:title>Blog - Alveolar Glottis</image:title>
    </image:image>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/blog-forte/2016/2/22/plosive-morphological-syntax-aslbc</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2016-02-22</lastmod>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/blog-forte/2016/2/22/frication-glwh8</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2016-02-22</lastmod>
    <image:image>
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      <image:title>Blog - Frication</image:title>
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  </url>
  <url>
    <loc>https://www.mmanalytics.tech/blog-forte/2016/2/22/velar-aspirations-gansp</loc>
    <changefreq>monthly</changefreq>
    <priority>0.5</priority>
    <lastmod>2016-02-22</lastmod>
    <image:image>
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      <image:title>Blog - Velar Aspirations</image:title>
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    <image:image>
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      <image:title>Blog - Velar Aspirations</image:title>
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  </url>
  <url>
    <loc>https://www.mmanalytics.tech/read-me</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2016-02-23</lastmod>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/reach-out</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2016-02-23</lastmod>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/partnerships</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2026-02-11</lastmod>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/755db04e-7c26-4544-b8dd-b9750d949658/hireroadlogo.jpeg</image:loc>
      <image:title>Partnerships - Make it stand out</image:title>
      <image:caption>2024-2026</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/6666963f-24ec-41f0-af56-580d9c5e45ff/coeuraj-logo.png</image:loc>
      <image:title>Partnerships - Make it stand out</image:title>
      <image:caption>2022-2024</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/9eb9538f-4275-407e-973c-03848eff81a9/nolk-logo.png</image:loc>
      <image:title>Partnerships - Make it stand out</image:title>
      <image:caption>2021-2022</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/1565821825059-NSTBZ241S0O35XMEI0H4/image-asset.png</image:loc>
      <image:title>Partnerships</image:title>
      <image:caption>2019-2020</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/1565822357960-TWDBGC6FH9T2EWE1K81U/eduonix.jpeg</image:loc>
      <image:title>Partnerships</image:title>
      <image:caption>2018-2019</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/1565822154482-1334TP4DA30M9RL3ALVO/download+%283%29.png</image:loc>
      <image:title>Partnerships</image:title>
      <image:caption>2017-2018</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/1565930965066-8S632F5ZX101WCLQZZPV/download+%282%29.png</image:loc>
      <image:title>Partnerships</image:title>
      <image:caption>2017</image:caption>
    </image:image>
    <image:image>
      <image:loc>https://images.squarespace-cdn.com/content/v1/5d54549a19c5d80001d09850/1565822052777-MMOZVCLV58WIQIVJFXZY/smule-logo-png-2-1.png</image:loc>
      <image:title>Partnerships</image:title>
      <image:caption>2016</image:caption>
    </image:image>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/connect</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2026-02-11</lastmod>
  </url>
  <url>
    <loc>https://www.mmanalytics.tech/connectdemo</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2024-08-23</lastmod>
  </url>
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