Softment

AI by Industry

AI for Customer Support

Deflect repetitive tickets with grounded answers, then escalate edge cases to humans with context intact.

Start smallFixed-scope pilot
Delivery1–2 weeks typical
IncludesSource + handoff
Support bot grounded in your docs and policiesTicket triage + routing with structured fieldsEscalation flows to humans with contextMonitoring, evals, and guardrails for stabilityWorkflow automation across helpdesk + CRM

Industry Problems

Where teams get stuck

Common bottlenecks we see before AI workflows are implemented.

Repetitive tickets

Support teams spend time answering the same questions across channels, slowing response times.

Inconsistent answers

Without grounding, assistants can guess or conflict with your policies, creating risk.

Slow routing and escalation

High-priority tickets get buried without reliable triage and structured fields.

Limited visibility

Quality and costs drift without eval baselines, logging, and alerting.

AI Solutions

What we build

Implementation-ready modules designed for reliability, safety, and real operations.

RAG support bot with citations

Ground responses in docs and policies, include citations, and fall back safely when uncertain.

Ticket triage and routing

Classify intent and urgency, populate structured fields, and route to the right queue.

Escalation with context

Hand off to humans with transcript, summary, and suggested next steps.

Monitoring + evals

Add tracing, quality measurement, and regression checks to prevent silent failures.

Stack

Suggested implementation stack

A practical stack we can adapt to your constraints and existing systems.

OpenAI / Claude (LLM)RAG (docs/policies) + citationsVector DB (pgvector / Qdrant)Helpdesk/CRM APIsGuardrails + eval baselinesMonitoring + alerts

Automations

Example automations

A few workflows that usually deliver ROI quickly.

Deflect FAQs with grounded answers

Auto-route tickets by intent and priority

Escalate edge cases with context handoff

Sync outcomes to CRM and dashboards

Monitor quality and cost over time

Standard

AI delivery standard

Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.

Logging + tracing

Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.

Guardrails + safety

Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.

Evals + regression tests

Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.

Cost + latency controls

Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.

Documentation + handoff

Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.

Security-first integration

Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.

Compare

Decision guides

Quick comparisons to help you choose the right approach before building.

FAQ

Frequently asked questions

Will this replace our support team?

No. The goal is to deflect repetitive tickets and improve routing, while escalating complex cases to humans with context preserved.

Can you connect to our helpdesk and CRM?

Yes. We can integrate with common helpdesk and CRM tools via API/webhooks. Scope depends on your plan/permissions and desired actions.

How do you reduce hallucinations?

We use grounding (RAG), validation, safer fallback patterns, and evaluation baselines to measure and improve quality.

Can we start with a small pilot?

Yes. A fixed-scope pilot is a common approach to validate ticket deflection and routing before scaling.

Ready to start?

Want an AI pilot for your workflow?

Start with a fixed-scope gig or request a tailored implementation plan for your systems.