Softment

AI Development

AI Chatbot Development Services

We build AI chatbots that do useful work—support deflection, lead qualification, and internal assistance—grounded in your data with safer responses and integration-ready delivery.

TimelineTypical: 2–8 weeks (scope-dependent)
Starting at€1.2k
Security-first AI integrations • Evals + logging + guardrails included

Overview

What this service is

This service delivers an AI chatbot tailored to your workflows: conversation design, web embed UI, and a backend that supports retrieval, analytics, and escalation paths.

We connect the bot to your knowledge sources (docs, help centre, PDFs, internal pages) and tune retrieval so answers stay grounded instead of guessing.

You get a production-ready implementation with monitoring hooks and handoff notes so your team can update content, improve prompts, and extend features after launch.

Benefits

What you get

Reduce repetitive support load

Deflect common questions and route complex issues to humans with better context.

Capture and qualify leads

Turn conversations into structured lead data with clear handoff to your CRM or email.

More accurate answers with RAG

Use your docs as the source of truth to reduce hallucinations and improve trust.

Better customer experience

Fast answers, clear escalation, and a conversation UX that feels intentional—not a toy.

Integration-ready architecture

Connect to ticketing, CRM, and automation tools with reliable workflows.

Maintainable handoff

You get source code and guidance for improving content and prompts over time.

Features

What we deliver

Conversation UX + web embed

A clean chat UI with clear states, suggested prompts, and escalation messaging when needed.

RAG retrieval setup

Ingestion, chunking, and retrieval configuration to ground responses in your documents.

Lead capture workflows

Structured fields, consent-aware capture, and delivery to email/CRM tools or your backend.

Guardrails and safer responses

Fallbacks, refusal patterns, and retrieval-first answering strategy to reduce risky output.

Basic analytics + feedback hooks

Logging and lightweight analytics to measure deflection, drop-offs, and common queries.

Deployment + handoff notes

Environment setup, rollout guidance, and documentation for ongoing improvements.

Process

How we work

1
2–4 days

Discovery

We define goals, escalation rules, and success metrics—then scope the first release.

2
2–6 days

Data preparation

We collect documents, set ingestion rules, and confirm access/permission constraints.

3
1–4 weeks

Build

We implement the chatbot UI, retrieval pipeline, and workflows with milestone demos.

4
3–7 days

Evaluation

We test accuracy, failure cases, and escalation behaviour to reduce unsafe responses.

5
2–4 days

Launch + Handoff

We deliver rollout notes and guidance for improving prompts and knowledge sources.

Tech Stack

Technologies we use

Core

OpenAI APIEmbeddingsVector DB (pgvector/Pinecone)LangChain (or equivalent)

Tools

Next.js / React UINode.js APIsAuth (optional)Rate limiting

Services

Sentry / loggingWebhook integrations

Use Cases

Who this is for

Customer support chatbot

Answer FAQs, guide troubleshooting, and escalate to humans with context when needed.

Lead qualification assistant

Collect requirements, budgets, timelines, and route leads into your CRM with structured notes.

Internal knowledge assistant

Help teams find policies, SOPs, and product knowledge quickly from internal docs.

Sales enablement bot

Respond with product details and positioning grounded in approved collateral and docs.

Product onboarding helper

Guide users through features with step-by-step answers tied to your documentation.

FAQ

Frequently asked questions

We use a retrieval-first approach (RAG), tune chunking and retrieval, and add fallback patterns so the bot doesn’t guess when the answer isn’t in your content.

Yes. We can integrate lead capture and escalation workflows with common tools using APIs and webhooks.

Yes. We can scope access control and ingestion rules based on your privacy and compliance requirements.

Yes. Many teams start with a support FAQ bot, then add more sources, workflows, and analytics once the core value is proven.

Yes. You receive full source code plus notes on how to update documents and improve responses over time.

Regional

Delivery considerations for your region

Compliance & Data (EU)

For Germany/EU delivery, we keep GDPR-first patterns: data minimisation, purpose-limited storage, and explicit access boundaries.

We can work under a DPA (template available on request) and implement pragmatic retention/deletion flows when needed.

  • GDPR-first architecture patterns (generic, no legal claims)
  • DPA template available on request
  • Retention/deletion and export flows where required
  • Least-privilege access and safe logging defaults
  • Documented data flows and access boundaries

Timezone & Collaboration (EU)

We align to EU working hours with CET-friendly collaboration windows and async progress updates.

We keep delivery predictable: weekly milestones, documented decisions, and clear scope control.

  • EU overlap with CET-friendly windows
  • Async-first delivery with written decisions
  • Weekly milestone demos and progress checkpoints
  • Clear change control to avoid surprises
  • Escalation path for blockers and risks

Engagement & Procurement (EU)

We support procurement-friendly engagements with clear scopes, milestone plans, and documentation that stakeholders can review.

For EU teams, we can structure invoices and milestones for EUR-based engagements where appropriate.

  • EUR-based engagements and invoicing options
  • Discovery-first option to reduce delivery risk
  • Milestone-based billing and scope sign-offs
  • Vendor onboarding documentation on request
  • Transparent change control and approvals

Security & Quality (EU)

We prioritise reliability: reviewable PRs, predictable releases, and tests that protect critical paths.

Performance budgets and clear release discipline keep the product stable as it grows.

  • CI-friendly testing: unit + integration + smoke tests
  • Performance budgets + bundle checks
  • Release checklist + rollback-safe deployments
  • Security checklist for auth and sensitive data flows
  • Observability hooks (logs + error tracking) ready for production
Ready to start?

Want an AI chatbot your team can trust?

Share your use case and knowledge sources. We’ll recommend the right RAG setup, integrations, and rollout plan.

Source code + update guidance included.