Prometheas Technologies
SolutionsAI & Data

AI copilot for enterprise workflows.

Prometheas builds enterprise copilots that sit inside real workflows: service desks, Salesforce service operations, ServiceNow operations, claims and case teams, shared-services groups, and internal knowledge estates. The focus is not a generic chatbot; it is a governed assistant that improves daily work with source grounding, permissions, evaluation, and human review.

RAG
Grounded retrieval
RBAC
Permission-aware access
Human
Review for sensitive actions
Managed
Quality tuning available
Expected outcomes
Faster knowledge lookup

Teams find policies, ticket context, account history, or operational guidance faster without leaving the workflow.

More consistent service work

Summaries, drafts, classifications, and recommendations follow governed sources and review paths rather than individual habits.

AI that can be operated

Quality, cost, usage, permissions, feedback, and escalation are visible enough for leaders to manage after launch.

What buyers are trying to solve

Pressures shaping
the buying decision.

  • Knowledge exists but work still slows down

    Teams have policies, tickets, cases, documents, and system records, but staff still spend too much time searching, summarizing, and stitching context together.

  • Generic chatbots do not fit enterprise workflows

    A standalone assistant can answer questions, but service teams need context, permissions, action boundaries, escalation, and audit history.

  • Sensitive workflows need control

    Regulated or customer-facing teams cannot let a model invent answers, expose restricted data, or take actions without review.

  • No quality standard for AI responses

    Leaders need evaluation sets, feedback loops, answer traceability, and production monitoring before a copilot can be trusted.

How Prometheas delivers

The plays we run
to ship safely.

  • Workflow-first copilot design

    We map the user journey, source systems, decisions, handoffs, risk levels, and human approval points before choosing the model or interface.

  • Grounded retrieval and permissions

    Answers are grounded in approved knowledge and operational data, with role-aware access and clear citations or source references where needed.

  • Human review for sensitive actions

    The copilot can summarize, draft, classify, recommend, and prepare next steps while humans approve high-risk or customer-visible actions.

  • Evaluation before scale

    We build scenario tests, expected-answer sets, red-team prompts, feedback capture, and quality dashboards before expanding usage.

Use cases

Where this
creates leverage.

  • Service desk copilots

    Summarize incidents, suggest next actions, retrieve known fixes, prepare handoffs, and route escalations inside ServiceNow or similar tools.

  • Salesforce service copilots

    Surface customer context, draft responses, summarize cases, recommend knowledge, and prepare follow-up tasks for service teams.

  • Claims and case copilots

    Read evidence, identify missing information, summarize documents, draft internal notes, and escalate decisions with an audit trail.

  • Internal knowledge copilots

    Answer employee or shared-services questions from governed policy, process, product, and operational knowledge sources.

Delivery shape

Sized to the
risk and scope.

  • Copilot opportunity assessment

    2-3 weeks to map workflows, users, source systems, risk tiers, permissions, and the best first copilot use case.

  • Governed copilot pilot

    8-12 weeks for one workflow with retrieval, permissions, evaluation, human review, and adoption instrumentation.

  • Production copilot rollout

    12-20 weeks for a broader release with integrations, monitoring, operating routines, feedback loops, and support handoff.

  • Managed copilot improvement

    Monthly quality review, prompt and retrieval tuning, cost control, model evaluation, and new workflow expansion.

Technology involved where needed

Supporting systems, not the main story.

We choose tools around ownership, risk, integration needs, and lifecycle cost. Buyers should see this as implementation support, not the definition of the solution.

Approved model providersRAG and vector retrievalServiceNow and SalesforceKnowledge bases and document storesPermission and identity systemsEvaluation and monitoring tooling
Capabilities in this solution

What the engagement includes.

  • Enterprise copilot discovery and workflow mapping
  • RAG architecture and governed knowledge retrieval
  • ServiceNow, Salesforce, portal, and internal-tool embedding
  • Role-based permissions and source-level access control
  • Prompt, model, and answer-quality evaluation
  • Human review queues, escalation paths, and audit logs
  • Production monitoring, cost controls, and managed improvement
Who you'll work with
KM
Kabir Malhotra
Practice Lead — Product Engineering
A product is not finished when it launches. It is finished when customers can use it and the business can run it.

Leads digital product engineering for customer portals, SaaS platforms, mobile apps, cloud modernization, and AI-enabled product experiences.

Full profile

AI Copilot on your roadmap?

30 minutes with Kabir Malhotra. No slides, no deck — a practical architecture sketch, scope estimate, and candid second opinion.

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