▣ Conversational · LLM · 2026
Chatbots that resolve, not deflect.
Tridence designs and ships customer-facing and internal chatbots—LLM-powered, retrieval-grounded, and wired into the systems where the answer actually lives. We build for resolution rate, not for "the bot said something."
Tailored · To your scope · No flat-rate menus
The honest part
A chatbot is not a feature. It is a support team.
Most "chatbot projects" fail because the bot was bolted onto a help-center page with no access to the order database, no escalation path, and no measurement. We do not ship bots that cannot resolve. We ship bots that connect to the system, log the outcome, and hand off cleanly when they should not be the one answering.
Demo · Embed · Forget
Hello, I am a friendly assistant. The bot reads marketing pages, hallucinates pricing, and dumps every hard question on a queue that already had a backlog.
This is the bot that gets turned off in 90 days.
Ground · Integrate · Measure
The bot is grounded in your real systems—orders, accounts, knowledge base, ticketing. Tools, retrieval, and guardrails are explicit. Every conversation is rated, logged, and feeds the next iteration.
This is the bot that earns its seat.
What we build
Six chatbot disciplines. One measured outcome.
Whether you need a customer-support agent, a sales assistant, or an internal copilot for your ops team, the work fits one of these tracks.
Customer support agents
Tier-1 deflection on web, app, SMS, and WhatsApp. Order lookup, account changes, returns, and warm hand-off to a human when the bot should step aside.
Sales & pre-sales assistants
Qualifying questions, product fit, pricing guidance, and booking flows—wired straight into your CRM so the lead lands in the right place with the right context.
Internal copilots & ops bots
Slack and Teams agents that answer policy questions, pull reports, kick off workflows, and write the first draft so your humans can edit instead of write from zero.
Voice & IVR replacement
Real-time voice agents for call deflection, after-hours coverage, and outbound. Latency budgets honored, fallback to a human within seconds when needed.
RAG & knowledge grounding
Document ingestion, chunking, embeddings, and retrieval that actually returns the right paragraph. Citations on by default. No "the bot said you have unlimited refunds."
Evals, guardrails & observability
Prompt regression suites, content filters, PII redaction, jailbreak monitoring, and a dashboard that tells you which intents are winning and which are wasting tokens.
How engagements start
Three entry points. One standard.
No SKUs, no flat-rate menus. Pick the front door that matches where you are; we size the work after a real conversation.
Conversation Audit
- Top 50 intents & resolution math
- Knowledge & data-source review
- Risk, PII, and compliance gaps
- 90-day build or rebuild plan
End-to-End Bot Build
- Design, RAG, tools, guardrails
- CRM / ticketing / order integrations
- Evals, dashboards, and hand-off
- Day-30 resolution target baked in
Continuous Bot Care
- Knowledge updates & re-indexing
- Intent & prompt regression
- Cost, latency, and quality SLOs
- Quarterly model & prompt reviews
How the work moves
Listen. Ground. Build. Measure.
Every engagement runs on the same loop. The names are unglamorous on purpose.
Real conversations first
We read your tickets, transcripts, and call logs before we touch a prompt. The top 50 intents are ranked by volume and resolvability, not by what is easy to demo.
Sources & tools
Knowledge base, order DB, CRM, ticketing—wired to retrieval and tool calls with citations. The bot can cite where every answer came from, on demand.
Design, evals & hand-off
Prompts, tools, guardrails, and a graceful escalation path are in place before launch. Eval suites catch regressions before users do.
Resolution & iteration
Resolution rate, CSAT, escalation rate, and cost per conversation on a real dashboard. Weekly tuning until day-30 targets land, then monthly after that.
The stack
Models, frameworks, and tools we ship with.
We pick tools we are willing to be on-call for. The list is short on purpose, and model-agnostic by design.
FAQ
Chatbot questions, answered honestly.
Will the bot make things up?
Less, when it is grounded in your real systems with retrieval and tool calls instead of free-form generation. We turn citations on, set refusal behavior for things outside scope, and run regression evals to catch drift before users do.
OpenAI, Anthropic, or open-source?
Whichever fits your data residency, latency budget, and cost target. We have shipped on all three. Most production bots end up multi-model: a strong model for hard intents, a cheaper one for simple ones.
How do you handle PII and compliance?
Redaction at the edge, scoped retrieval, audit logs, and provider terms reviewed before integration. We have shipped under HIPAA and SOC 2. Compliance is a design constraint, not a final-quarter scramble.
What about hallucinations and edge cases?
Eval suites, content filters, PII guards, and a hard fallback to a human when the bot is not confident. The bot is allowed to say "I do not know"—and it should.
Can it integrate with our existing helpdesk?
Yes—Zendesk, Intercom, Salesforce Service Cloud, HubSpot, Freshdesk, Kustomer. Hand-off carries the full conversation and any extracted intent so your agents do not start from zero.
What does it cost?
Tailored to scope. There is no flat-rate menu. We size the work after a 15-minute discovery and a feasibility pass, never before.
Got a support queue, a sales funnel, or an internal team that needs a copilot?
Bring a week of transcripts and your top three intents. Fifteen minutes, real engineers, no slide deck.
Jacksonville (HQ) · Chicago · Nationwide