Turn AI potential into measurable business outcomes.
Mirketa helps enterprise teams identify high‑value AI use cases, build a solid business case & roadmap, and deliver production‑ready AI solutions—secure, compliant, and integrated with your systems.
Meet a senior ServiceNow Developer
What We Do
- Use‑Case Discovery: Sessions to surface AI opportunities tied to KPIs and constraints.
- Business Case & Roadmap: ROI/TCO modeling, risk assessment, data readiness, and staged plan.
- Solution Architecture: RAG, agents, copilots, and predictive pipelines across your data/app stack.
- Build & Integrate: Secure LLM apps, automations, and analytics that plug into ERP/CRM/ITSM/HCM tools.
- Operate & Improve: Reliability engineering, monitoring, governance, and enhancements.
Platforms & Tooling We Work With
- Models: OpenAI (GPT‑4o), Azure OpenAI, Google Vertex AI (Gemini), AWS Bedrock (Claude, Llama, Cohere), Anthropic Claude.
- Frameworks: LangChain, LlamaIndex, agent frameworks with function/tool calling.
- Vector/Search: Pinecone, Weaviate, Milvus, FAISS, Qdrant, Elasticsearch/OpenSearch.
- Data & MLOps: Databricks, Snowflake, BigQuery, dbt; MLflow, Weights & Biases; Vertex/SageMaker pipelines.
- Security & Guardrails: Prompt‑injection defenses, PII redaction, content moderation, evals, audit logging.
- Enterprise Apps: ServiceNow, Salesforce, Oracle Fusion, Workday, Microsoft 365, Google Workspace.
Services by Stage
Understand
Stakeholder interviews, process mapping, KPI linking, data readiness & compliance assessment.
Decide
ROI/TCO, risk & controls (security, legal, governance), 90‑day and 12‑month roadmap.
Design
Target architecture for RAG, agents/copilots; ingestion/chunking/embedding patterns; pilot backlog.
Build
LLM app development (chat, Q&A, summarization, extraction, copilots), integrations to core systems, CICD, observability, cost controls.
Run
Human‑in‑the‑loop, feedback loops, evals & monitoring, SLA‑aligned support, quarterly upgrades.
Integrated Risk Management (IRM/GRC)
Policy/risk controls, compliance, vendor risk, audit workflows.
Industry‑Focused AI Solutions
Technology (Software/SaaS):
Developer & Support Copilots; product intelligence from telemetry and feedback.
Healthcare
Clinical documentation support with PHI controls; operations analytics blending EHR + HR/Finance.
Finance & Insurance
KYC/AML extraction and routing; narrative close/reporting copilots with approvals.
Education
Student services assistants and faculty workbenches; research compliance checks.
Nonprofit
Donor insights, grant narrative assistance, volunteer scheduling copilots.
eCommerce & Retail
Merchandising copilot for PDP content; order/return service automation.
Manufacturing
Quality/CAPA insights, RAG over manuals, supplier contract summarization.
Education
Student services assistants and faculty workbenches; research compliance checks.
Integration & Data
- Integration Patterns: Integration Hub spokes, REST/SOAP, webhooks, event‑driven orchestration, and RPA for legacy.
- Common Systems: Identity/SSO, SIEM/SOAR, monitoring, SCCM/Intune, HRIS/Payroll, CRM/CTI, ERP/Finance, data warehouses/lakes.
- Data Governance: CMDB strategy, service mapping, data quality SLAs, and retention policies.
Onshore–Offshore Delivery Model
- Onshore: Product owners, solution architects, UX, and change leadership; direct engagement with process owners and execs.
- Offshore: Certified ServiceNow developers for config, flows, integrations, tests, and documentation—executing non‑critical work in follow‑the‑sun cycles.
- Benefits: Lower cost, faster throughput, and elasticity to handle peaks without adding headcount.
Reference Architectures We Implement
- RAG for Enterprise Knowledge: ingestion → chunking/embedding → vector store → guarded generation with citations and feedback.
- Agentic Workflows: policy‑bounded agents that call tools/APIs/DBs with human approval gates.
- Document Intelligence: OCR + layout parsing → extraction → validation queue → system updates.
- Analytics + GenAI: data pipeline → metrics/segments → narrative generation & what‑ifs.
Security, Compliance & Governance
- Data minimization and PHI/PII redaction before model calls; tenant isolation and encryption.
- Prompt/output filtering, jailbreak/injection defenses, audit trails, and RBAC policies.
- Domain‑specific evals for accuracy/bias/toxicity; human‑in‑the‑loop where needed.
Reference Architectures We Implement
- RAG for Enterprise Knowledge: ingestion → chunking/embedding → vector store → guarded generation with citations and feedback.
- Agentic Workflows: policy‑bounded agents that call tools/APIs/DBs with human approval gates.
- Document Intelligence: OCR + layout parsing → extraction → validation queue → system updates.
- Analytics + GenAI: data pipeline → metrics/segments → narrative generation & what‑ifs.
Sample Engagements & Outcomes
- Support Copilot for IT: 25–35% ticket deflection; faster MTTR via RAG over KB/runbooks.
- Finance Narrative Close: hours saved per close with auto‑drafted commentary and reconciliation summaries.
- Recruiting Assistant: reduced time‑to‑screen via structured extraction and compliant summaries.
- Commerce Content Studio: brand‑guarded PDP/FAQ generation; measurable conversion lift.
FAQs
Which model should we choose?
Platform‑agnostic selection based on data sensitivity, latency, cost, and capability (OpenAI, Azure OpenAI, Vertex AI, Bedrock, Claude).
How do you ensure accuracy?
RAG with citations, constrained prompting, domain evals, and human‑in‑the‑loop reviews.
Can you integrate with our systems?
Yes—APIs/events for ServiceNow, Oracle, Workday, Salesforce, and data platforms.
How do you control costs?
Cache/embedding reuse, model routing, token budgets, and observability.
Featured Insights
Ready to build AI that your business trusts?
Book an AI Use‑Case Workshop or speak with an Enterprise AI Architect to shape your business case and roadmap.

