Table of Contents

What is a chat agent in Adhesives & Sealants?

In Adhesives & Sealants, a chat agent is an AI system that understands and answers product and application questions using the existing technical documentation – for example technical data sheets (TDS), safety data sheets (SDS), and application or installation guides. Instead of customers or distributors searching PDF libraries or waiting for email replies, the chat agent interprets requirements like substrates, temperature, open time, curing conditions, and certifications, then responds in natural language within seconds.

How Does It Compare to Traditional Approaches?

Approach Response Time Technical Depth Availability Scalability
FAQ page Instant but limited Very shallow content 24/7, static No personalization
Classic rule-based chatbot Instant, scripted Fixed decision trees 24/7, predefined flows Hard to maintain variants
Human technical support Minutes to days High, expert-level Business hours, limited Linear with headcount
AI chat agent (docs-based) Seconds Reads full TDS/SDS 24/7 across regions Handles thousands of chats

For Adhesives & Sealants, the challenge is not a lack of information but accessing the right specification at the right moment: mixing ratios, VOC limits, tensile strength, or compatibility with specific substrates. A chat agent can navigate complex product families, legacy formulations, and regional variants in real time, so customers, distributors, and internal teams get consistent answers without manually searching through dozens of PDFs or emailing different experts.

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Why documentation alone is not enough in Adhesives & Sealants

A typical Adhesives & Sealants portfolio spans hundreds of formulations, each with its own TDS, SDS, and regional variants. Customers and distributors often struggle to locate the exact document for a given substrate, curing condition, or certification, then still have to interpret tables of performance data and limitations. Small details like surface preparation or allowable temperature range can decide whether an application succeeds or fails.

Technical service teams receive recurring questions that are already documented: which adhesive for a specific plastic–metal combination, how to replace a discontinued product, whether a sealant meets a particular fire or food-contact standard, or how to handle overcoating and rework. Yet these teams are under pressure to do more with less, while 79% of service leaders expect AI agents to become fundamental to their operations.[3]

Response times are especially painful in cross-time-zone projects. A construction site may be waiting on clarification about joint dimensions on a Friday evening, or an automotive supplier in another region needs confirmation on heat resistance before starting a production trial. When experts are available only in one time zone, projects stall, and customers turn to competitors that respond faster.[2]

At the same time, customers remain wary of generic chatbots that cannot handle complex technical questions. In Germany, 62% of online customers still prefer human contact over chatbots for service issues, largely due to poor experiences with simplistic systems.[5] Adhesives & Sealants companies must therefore find a way to provide instant, precise answers while keeping human experts available for genuinely complex, high-value conversations.

The problem explained in 2 minutes

What Users say

Tim Neubacher
Tim Neubacher

Tim Neubacher

Tim Neubacher

svt Brandschutz GmbH Head of Technology - svt Brandschutz GmbH

The fire protection chatbot can answer even the most complex questions about our products with a level of quality and speed that is absolutely fascinating.
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Practical chat agent use cases for Adhesives & Sealants

Six concrete ways Adhesives & Sealants companies can turn existing TDS, SDS, and application know-how into always-on digital support – across sales, technical service, and operations.

Product selection assistant for substrates and conditions

Technical Service / Application Engineering

The Idea

The Idea

A chat agent guides customers, distributors, and internal sales through product selection based on substrate, joint type, temperature, curing time, and certification needs. It asks a few targeted questions, then proposes suitable adhesives or sealants and highlights key parameters like open time, gap-filling ability, and compatibility with primers.

What You Need

  • Structured product master data with key properties (chemistry, substrates, cure profile, approvals).
  • Up-to-date TDS library, ideally tagged by region and application.
  • Optional: CRM or e-commerce integration to generate quotes or sample requests.

Instant SDS & regulatory information finder

Regulatory Affairs / HSE

The Idea

The Idea

The chat agent answers safety and compliance queries: finds the correct SDS version for a country, clarifies hazard statements, storage conditions, or transport classifications, and explains regulatory changes in plain language. Internal staff and customers get precise guidance without waiting for HSE teams.

What You Need

  • Central SDS repository with versioning and country/language mapping.
  • Regulatory summaries (REACH, CLP, VOC, food-contact approvals) in document form.
  • Optional: Integration with SDS authoring system for automatic updates.

Troubleshooting for failures and complaints

Quality / Customer Service

The Idea

The Idea

When a bond fails or a seal cracks, the chat agent walks users through structured troubleshooting: asking about surface preparation, curing time, humidity, joint design, and load. It then proposes likely root causes and references the relevant guidance in manuals or complaint-handling procedures.

What You Need

  • Documented troubleshooting guides and complaint case examples.
  • Access to application manuals and processing instructions.
  • Optional: Connection to complaint-management system to log new cases.

Digital companion for installers and contractors

Field Service / Training

The Idea

The Idea

On-site installers and contractors use the chat agent as a pocket guide: asking about joint dimensions, recommended application temperature, overpainting, or compatibility with specific building materials. It can also surface short training videos or step-by-step instructions directly from existing manuals.

What You Need

  • Installation manuals and training documents in digital form.
  • Mobile-optimized access (QR codes on packaging, jobsite posters).
  • Optional: Integration with a learning platform for tracking training completion.

Technical lead qualification for B2B sales

Sales / Business Development

The Idea

The Idea

A website or portal chat agent qualifies inbound requests by collecting key application data – materials, temperature cycles, mechanical loads, process constraints – and suggesting suitable solutions. Qualified leads, including all technical details, are then passed to sales or application engineering for follow-up.

What You Need

  • Clear mapping from application parameters to product families.
  • Templates for qualification questions aligned with the sales process.
  • Optional: CRM integration (for example, lead creation in a system like Salesforce).

Internal knowledge hub for formulation and R&D teams

R&D / Product Management

The Idea

The Idea

Internally, a chat agent helps formulation and product management teams find existing formulations, change histories, and performance data from lab reports and historical projects. It reduces time spent searching archives and supports faster responses to custom development requests.

What You Need

  • Access to internal reports, formulation overviews, and project documentation.
  • Basic tagging of documents by product family and use case.
  • Optional: Integration with PLM or document management systems.

Measured outcomes when chat agents support Adhesives & Sealants teams

+3%

Revenue Growth

In Adhesives & Sealants, +3% additional revenue typically comes from capturing more qualified opportunities and reducing drop-off when customers cannot find the right product. Faster, AI-supported guidance increases conversion on digital channels and enables sales teams to focus on high-potential projects, aligning with studies that link AI in service to double-digit efficiency and cost improvements.[3][4]

4x

Customer Satisfaction

Customers expect instant answers even for complex technical questions. When chat agents provide accurate, context-aware responses 24/7, satisfaction can reach up to four times that of experiences with basic chatbots, which currently deliver only around 50% satisfaction versus 86% for humans.[5] Using conversational AI that is trained on TDS, SDS, and application guides helps close this gap.[1]

3-5h

Saved Weekly per Agent

Technical service engineers in Adhesives & Sealants spend many hours each week repeating the same explanations about substrate compatibility, curing profiles, and certifications. Automating recurring questions with AI assistants typically frees 3–5 hours per person per week, in line with studies that report around 20% reductions in service workload and resolution time when AI agents are deployed.[3][7]

+17%

Team Happiness

When routine queries are handled by AI, Adhesives & Sealants experts can focus on challenging projects and value-adding work. Surveys show that around 80% of employees say AI tools improve their work quality and make interactions more efficient.[10] This shift away from repetitive inquiries supports meaningful gains in motivation and team satisfaction, often measured in the low double-digit range.

How it works

From zero to a live chat agent – typically within 5–10 business days.

Upload knowledge base
Configure and integrate
Deploy and optimize
Upload knowledge base
Configure and integrate
Deploy and optimize
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Common pitfalls when introducing chat agents in Adhesives & Sealants

1

Relying only on marketing brochures instead of technical documentation

Many companies start by uploading only brochures or website copy. This limits the chat agent to generic statements and prevents it from answering real application questions. Instead, prioritize TDS, SDS, application guides, and troubleshooting documents. Marketing material can be added later for tone and positioning, but technical depth must come first.

2

Expecting 100% automation from day one

Conversational AI in customer service typically augments human agents rather than fully replacing them.[2] In Adhesives & Sealants, where safety and performance are critical, a realistic goal is to automate 40–60% of recurring questions after 90 days, while routing edge cases to human experts. Plan for regular review cycles instead of assuming the system is finished at go-live.

3

Ignoring product variants, regions, and discontinued items

Adhesives & Sealants portfolios often include regional formulations, private labels, and legacy products. If these relationships are not modeled, the chat agent may suggest outdated products or fail to propose replacements. Maintain mappings between global and regional SKUs, successor products, and approval differences, and keep a clear rule set for how the assistant should respond when an item is discontinued.

4

Treating the project as an IT experiment, not a service and application project

IT can provide infrastructure, but the real value comes from the knowledge held by technical service, HSE, sales, and product management. If these stakeholders are not involved, the assistant will miss crucial context like typical application pitfalls or regulatory nuances. Organize short, focused workshops with business experts to define use cases, escalation rules, and success metrics.

5

Not defining clear escalation and handover rules

Without defined boundaries, a chat agent may attempt to answer questions that require human judgment, such as liability-critical recommendations or non-standard formulations. Establish clear criteria for escalation (e.g. missing documentation, safety-critical topics, large-volume opportunities), specify how and where handovers occur, and communicate this transparently to users to maintain trust.[5]

Cost–benefit analysis: chat agents vs. technical staff in Adhesives & Sealants

Technical customer service and application engineering roles in Adhesives & Sealants are highly skilled and hard to scale. At the same time, many of their incoming questions are repetitive and already answered in TDS, SDS, and application guides. Comparing human roles with an AI-based chat agent helps quantify where automation is economically sensible.[3]

Technical Customer Service Engineer Application Engineer / Field Technical Service Chat Agent (Professional)
Annual cost €65,000–€85,000 incl. overhead €70,000–€95,000 incl. overhead €5,988 + €2,999 setup
Availability Business hours, limited overtime Project-based, travel constraints 24/7/365
Languages 1–2 languages 1–3 languages 80+
Simultaneous requests 1–3 parallel cases Limited by travel & calls Unlimited
Vacation / sick leave 25–30 days/year + sick leave 25–30 days/year + sick leave None
Onboarding time 3–6 months to full productivity 6–9 months incl. product training 5–10 days
Knowledge retention Walks out if employee leaves Partly in reports, mostly tacit Permanent, always up to date

The Reruption Chat Agent (Professional) plan costs €499 per month plus €2,999 setup, or €5,988 per year excluding setup. Compared to a single technical service engineer, this is a fraction of the annual cost and becomes economically attractive at roughly 2–3 additional resolved requests per day that would otherwise require human time. The goal is not to replace people, but to let experts focus on high-value engineering and customer collaboration while the chat agent handles repetitive, documentation-based questions 24/7 in over 80 languages.

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How a mid-size Adhesives & Sealants manufacturer automated 55% of technical inquiries in 90 days

Industry Adhesives & Sealants
Employees 650
Products 1,800+ adhesive & sealant SKUs
Deployment 7 business days

The Challenge

A European Adhesives & Sealants manufacturer with around 1,800 SKUs served construction, transportation, and industrial customers through distributors and direct OEM relationships. The five-person technical service team received 2,500–3,000 inquiries per month about product selection, substrate compatibility, and SDS details. Many questions repeated content already available in TDS and SDS, but customers and internal sales struggled to find the right information, especially outside European business hours.

The Solution

The company implemented a documentation-based chat agent that ingested TDS, SDS, application manuals, and an internal FAQ collection. Within 7 business days, the assistant was embedded on the website, distributor portal, and internal sales portal. It handled common topics such as selecting adhesives for specific material combinations, explaining curing conditions, and locating the correct SDS version by product, country, and language. Escalation rules ensured that safety-critical or unclear cases were routed to human experts.[7]

The Results

  • 55% of incoming technical questions fully answered by the chat agent within 90 days, based on a sample of tagged conversations.
  • Average first-response time reduced from hours to seconds for documentation-based questions, improving service levels for global customers.[3]
  • 3–4 hours saved per week per technical service engineer, allowing more time for complex investigations and key-account support.[10]
  • 30% increase in qualified digital leads from the website and distributor portal, as more visitors completed guided product selection dialogs.
  • Noticeable uplift in team satisfaction, with internal surveys showing experts felt less burdened by repetitive questions and more focused on challenging projects.
“We were surprised how quickly the assistant handled real substrate and application questions directly from our TDS and SDS. Instead of answering the same emails again and again, our team now spends time on complex projects and new developments.” - Head of Technical Customer Service
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Is a chat agent a good fit for your Adhesives & Sealants business?

A good fit

  • Broad product portfolio with hundreds of adhesives and sealants, frequent launches, and many regional variants, where customers and internal staff struggle to find the right TDS or SDS.
  • Significant support volume of at least 200–300 technical or safety-related inquiries per month via email, phone, or web forms, often repeating similar questions.
  • Established documentation practices such as up-to-date TDS/SDS libraries, application manuals, and basic FAQs that can serve as input for the assistant.
  • International customer base with distributors, OEMs, or contractors in multiple time zones and a need for multi-language support beyond the main office hours.
  • Digitalization focus where sales, technical service, and HSE teams are actively looking for ways to improve response speed, standardize answers, and collect better data from inquiries.

Not the right fit (yet)

  • Very low inquiry volume with fewer than 20 technical or safety questions per month, where manual handling remains efficient and automation would not reach breakeven.
  • Highly bespoke, one-off formulations only without stable product lines or reusable documentation, making it hard for an assistant to provide repeatable guidance.
  • Fragmented or outdated documentation where TDS, SDS, and manuals are missing, inconsistent, or not approved – these foundations should be addressed before deploying AI on top.

Security & Compliance

Chat agents for industrial use must meet strict data protection standards. These are the key requirements.

GDPR-Compliant

Full compliance with EU General Data Protection Regulation. Data processing agreements included. Regular audits and documentation.

Hosted in Germany

All data processed and stored on German servers. No data transfer outside the EU. Intellectual property stays where it belongs.

Enterprise-Grade Encryption

AES-256 encryption at rest, TLS 1.3 in transit. Product documentation and customer conversations are fully protected.

No Model Training

Data is never used to train AI models. It is exclusively used to answer customer questions. Nothing else.

Frequently Asked Questions

Yes, if it is built on the right data. Modern conversational AI can interpret complex documentation such as TDS, SDS, and application manuals to answer detailed questions about substrates, curing conditions, certifications, and processing steps.[1][9] The key is to provide high-quality, up-to-date documents and to define clear boundaries for when the assistant should escalate to human experts.

The assistant can be configured with mappings between global and regional SKUs, language and country-specific SDS, and successor products. When a user asks about a discontinued adhesive or sealant, it can propose approved replacements or prompt for more application details before suggesting alternatives. Maintaining this mapping in a simple reference file or system ensures that recommendations stay current and compliant.

By design, the assistant should transparently admit when it lacks information or when a question touches on safety- or liability-critical topics. In those cases, it collects the necessary context (product, application, volumes, location) and forwards the request to the appropriate technical service, HSE, or sales contact. This hybrid approach reflects best practices for conversational AI in complex B2B environments.[2][5]

Yes. Typical integrations for Adhesives & Sealants companies include SDS and document management systems for always-current safety data, CRM or marketing automation for lead capture, and e-commerce or portal platforms for product availability and pricing. Industry experience shows that combining conversational AI with existing platforms significantly improves customer experience and internal efficiency.[3][9]

For most Adhesives & Sealants companies with a reasonably structured document landscape, deployment typically takes **5–10 business days** from initial document delivery to a first usable version. This includes ingesting TDS/SDS and manuals, configuring escalation rules, and embedding the assistant on selected channels. Further optimization continues after go-live based on real user interactions.[7]

Reruption Chat Agent is offered in three tiers:

  • Starter: €99/month plus €799 one-time setup
  • Professional: €499/month plus €2,999 one-time setup
  • Enterprise: Custom pricing for larger deployments and advanced requirements

The Professional plan is typically suitable for mid-size Adhesives & Sealants companies and includes all core features needed for 24/7 multilingual support.

No. Reruption does not rely on a standard retrieval-augmented generation (RAG) pipeline. Instead, it uses a proprietary architecture optimized for **stable, documentation-grounded answers** from technical sources like TDS, SDS, and manuals. This approach is designed to minimize hallucinations, provide traceability back to source documents, and make it easier to comply with requirements such as the EU AI Act’s transparency obligations.[8]

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Real-World Chatbot Case Studies

How companies worldwide use chat agents and AI in customer support.

Amazon

E-commerce
In the vast e-commerce landscape, online shoppers face significant hurdles in product discovery and decision-making. With millions of products available, customers often struggle to find items matching their specific needs, compare options, or get quick answers to nuanced questions about features, compatibility, and usage.

Solution

Amazon developed Rufus, a generative AI-powered conversational shopping assistant embedded in the Amazon Shopping app and desktop. Rufus leverages a custom-built large language model (LLM) fine-tuned on Amazon's product catalog, customer reviews, and web data, enabling natural, multi-turn conversations to answer questions, compare products, and provide tailored recommendations.

Ergebnisse

  • 60% higher purchase completion rate for Rufus users
  • $10B projected additional sales from Rufus
  • 250M+ customers used Rufus in 2025
  • Monthly active users up 140% YoY
  • Interactions surged 210% YoY
  • Black Friday sales sessions +100% with Rufus
  • 149% jump in Rufus users recently
Read case study →

Bank of America

Banking
Bank of America faced a high volume of routine customer inquiries, such as account balances, payments, and transaction histories, overwhelming traditional call centers and support channels. With millions of daily digital banking users, the bank struggled to provide 24/7 personalized financial advice at scale, leading to inefficiencies, longer wait times, and inconsistent service quality.

Solution

Bank of America developed Erica, an in-house NLP-powered virtual assistant integrated directly into its mobile banking app, leveraging natural language processing and predictive analytics to handle queries conversationally. Erica acts as a gateway for self-service, processing routine tasks instantly while offering personalized insights, such as cash flow predictions or tailored advice, using client data securely.

Ergebnisse

  • 3+ billion total client interactions since 2018
  • Nearly 50 million unique users assisted
  • 58+ million interactions per month (2025)
  • 2 billion interactions reached by April 2024 (doubled from 1B in 18 months)
  • 42 million clients helped by 2024
  • 19% earnings spike linked to efficiency gains
Read case study →

Capital One

Banking
Capital One grappled with a high volume of routine customer inquiries flooding their call centers, including account balances, transaction histories, and basic support requests. This led to escalating operational costs, agent burnout, and frustrating wait times for customers seeking instant help.

Solution

Capital One addressed these issues by building Eno, a proprietary conversational AI assistant leveraging in-house NLP customized for banking vocabulary. Launched initially as an SMS chatbot in 2017, Eno expanded to mobile apps, web interfaces, and voice integration with Alexa, enabling multi-channel support via text or speech for tasks like balance checks, spending insights, and proactive alerts.

Ergebnisse

  • 50% reduction in call center contact volume by 2024
  • 24/7 availability handling millions of interactions annually
  • Over 100 million customer conversations processed
  • Significant operational cost savings in customer service
  • Improved response times to near-instant for routine queries
  • Enhanced customer satisfaction with personalized support
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Commonwealth Bank of Australia (CBA)

Banking
As Australia's largest bank, CBA faced escalating scam and fraud threats, with customers suffering significant financial losses. Scammers exploited rapid digital payments like PayID, where mismatched payee names led to irreversible transfers.

Solution

CBA deployed a hybrid AI stack blending machine learning for anomaly detection and generative AI for personalized warnings. NameCheck verifies payee names against PayID in real-time, alerting users to mismatches. CallerCheck authenticates inbound calls, blocking impersonation scams. Partnering with H2O.ai, CBA implemented GenAI-driven predictive models for scam intelligence.

Ergebnisse

  • 70% reduction in scam losses
  • 50% cut in customer fraud losses by 2024
  • 30% drop in fraud cases via proactive warnings
  • 40% reduction in contact center wait times
  • 95%+ accuracy in NameCheck payee matching
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Duolingo

EdTech
Duolingo, a leader in gamified language learning, faced key limitations in providing real-world conversational practice and in-depth feedback. While its bite-sized lessons built vocabulary and basics effectively, users craved immersive dialogues simulating everyday scenarios, which static exercises couldn't deliver .

Solution

Duolingo launched Duolingo Max in March 2023, a premium subscription powered by GPT-4, introducing Roleplay for dynamic conversations and Explain My Answer for contextual feedback . Roleplay simulates real-life interactions like ordering coffee or planning vacations with AI characters, adapting in real-time to user inputs.

Ergebnisse

  • DAU Growth: +59% YoY to 34.1M (Q2 2024)
  • DAU Growth: +54% YoY to 31.4M (Q1 2024)
  • Revenue Growth: +41% YoY to $178.3M (Q2 2024)
  • Adjusted EBITDA Margin: 27.0% (Q2 2024)
  • Lesson Creation Speed: 10x faster with AI
  • User Self-Efficacy: Significant increase post-AI use (2025 study)
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