AI CUSTOMER SUPPORT AGENT

UK businesses deploying AI customer support tools without a GDPR-compliant data processing agreement in place, without the FCA-required AI disclosure for financial services clients, and without any measurement of whether the AI deflection rate justifies the licence cost are taking on compliance risk while leaving performance gains unmeasured

Ignited Nepal deploys Intercom Fin, Zendesk AI, and custom AI support agents for UK businesses with GDPR data processing agreements, ICO guidance compliance, FCA communication rules applied, and deflection rate measurement built in from day one.

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This is for you if

Who This Is For

UK financial services businesses operating under the FCA Consumer Duty framework are required to demonstrate that every client communication, including those handled by automated systems, meets the standards of clarity, fairness, and suitability the Duty requires. Most IFAs, mortgage brokers, and insurance firms that have deployed Intercom or Zendesk AI have done so without a formal Consumer Duty review of the AI's response behaviour. The AI is answering client enquiries about products, processes, and eligibility, and in many cases, no one has reviewed whether those responses meet the standard the FCA would expect. The risk is not theoretical. An AI that provides an inaccurate or misleading response to a retail client enquiring about a financial product is generating a compliance record of that response in the ticketing system. Consumer Duty requires businesses to have oversight of client communications, and that oversight cannot be claimed if the AI has been running without configuration review, disclosure language, or documented escalation paths for complex financial queries. Ignited Nepal addresses this specifically, building the Consumer Duty framework into the AI deployment rather than assuming existing tools are already configured correctly.

UK e-commerce businesses frequently purchase Intercom or Zendesk subscriptions that include AI support features without completing the configuration required to activate them. The platform is installed, human agents are using the inbox, but Intercom Fin has never been turned on or the knowledge base is empty. The business is paying for AI capability while the support team manually responds to queries about order status, returns policy, delivery timelines, and product availability. These are precisely the query types that AI resolves accurately and at volume. The gap is not a strategic decision in most cases. It is a configuration backlog. The team that purchased Intercom did not have the time or the internal expertise to build the knowledge base, configure the AI resolution threshold, set up the escalation triggers, and measure the deflection outcome. Ignited Nepal completes this configuration in a structured engagement, builds the knowledge base to the standard Intercom Fin requires to achieve high resolution rates, and delivers a measurement framework so the support manager can see exactly what the AI is and is not resolving.

UK SaaS companies typically process personal data from multiple customer types across their support platform. When a customer submits a support ticket, that ticket contains personal data. When an AI model processes that ticket to classify, respond to, or route it, the AI vendor is acting as a data processor under UK GDPR. Article 28 requires that the controller and processor have a written Data Processing Agreement in place before that processing begins. Most UK SaaS businesses have not executed a specific DPA review for their AI support tools. The standard terms of service from Intercom or Zendesk include some DPA provisions, but they are not always specific to the AI processing features, and they do not address the international transfer obligations that arise when a US-based AI vendor processes UK customer personal data. The standard contractual clauses required for UK GDPR-compliant international transfers must be in place. Ignited Nepal provides guidance on the DPA requirements specific to each AI vendor and works with the client's legal team or DPO to ensure the documentation is complete before the AI handling customer data is activated.

UK professional services firms, particularly those handling client-sensitive information such as legal matters, financial accounts, or business consulting engagements, frequently delay AI support deployment not because of cost but because of GDPR uncertainty. The question of whether an AI system can legally process client communications in a professional services context is genuinely complex, and without specific guidance, the cautious default is to avoid deployment. This caution is understandable but it is resulting in support teams manually handling query volumes that AI could manage. The answer to whether AI customer support can be deployed in a UK professional services context is almost always yes, subject to proper documentation and configuration. The GDPR does not prohibit AI support deployment. It requires that the data processing is documented, the legal basis is established, and the customer is informed. Ignited Nepal provides the compliance framework that allows professional services firms to deploy AI support with confidence, addressing the specific concerns around client confidentiality, data minimisation, and transparency that are relevant to the sector.

What's broken

What's Broken

GDPR Data Processing Agreements with AI support vendors are not in place

UK GDPR Article 28 requires that a written Data Processing Agreement exists between the data controller (the business) and any data processor (the AI vendor) before personal data processing begins. This is not a recommendation or a best practice. It is a legal requirement, and the ICO has the power to issue enforcement notices and financial penalties where it is not met. When a business uses Intercom Fin or Zendesk AI to handle customer support queries, the AI vendor is processing personal data contained in those tickets. Name, email address, account details, and the content of the customer's enquiry are all personal data under the UK GDPR definition. The absence of a DPA means that processing is occurring without the documented legal basis the law requires. The complication for UK businesses is that both Intercom and Zendesk are US-headquartered companies. Their standard terms of service include Data Processing Addenda, but these documents are frequently signed without review, and they do not always address the specific AI features that have been activated. The AI features in Intercom Fin and Zendesk AI may involve data being processed by third-party AI models, including OpenAI or other large language model providers, that are not explicitly named in the DPA the business has signed. UK GDPR requires that sub-processors are identified and that the controller has approved their use. For cross-border transfers from the UK to the US, the UK International Data Transfer Agreement (IDTA) or the addendum to the EU standard contractual clauses must be in place. Most UK businesses using Intercom or Zendesk AI have not verified that their specific DPA covers the AI processing, the sub-processors involved in that processing, or the international transfer mechanisms that apply. The risk is that the AI is processing personal data right now on a legal basis that would not withstand ICO scrutiny.

FCA-regulated UK businesses have not applied Consumer Duty requirements to AI-handled client support

The FCA Consumer Duty, which came into full effect for open products and services in July 2023, requires that all client communications deliver good outcomes for retail customers. This requirement applies to every touchpoint in the client relationship, including automated ones. When an AI agent responds to a retail client's enquiry about their insurance policy, their mortgage options, or their investment account, that response is a client communication subject to the Consumer Duty standard. The Duty requires that the communication is clear, that it does not mislead, that it is appropriate to the client's needs, and that it supports good decision-making. An AI that is not configured with these requirements in mind is generating client communications that may fail the Consumer Duty test on each of these dimensions. The specific Consumer Duty failures that AI support deployments commonly produce include: responses that describe a financial product in terms that are accurate but not understandable to a retail client; responses that fail to recommend escalation to a human adviser when the complexity of the query warrants it; and responses that do not disclose that the client is interacting with an AI. The FCA's Consumer Duty guidance makes clear that firms must monitor outcomes and take action where they identify that communications are not delivering the standard the Duty requires. For a firm whose AI is handling hundreds of client enquiries per week, the absence of a Consumer Duty review of that AI's configuration is a significant gap. The monitoring obligation requires that the firm knows what the AI is saying and that it has assessed whether those responses meet the Duty's standards.

Intercom Fin or Zendesk AI is installed but the knowledge base is unstructured or empty

The single most common reason that Intercom Fin achieves low deflection rates in UK deployments is that the knowledge base it draws on is either empty, sparsely populated, or structured for human reading rather than AI retrieval. Intercom Fin and Zendesk AI are retrieval-augmented generation systems. Their ability to resolve a customer query accurately depends entirely on the quality and coverage of the knowledge base they have access to. If the knowledge base has ten articles that are each 2,000 words long and structured as narrative prose, the AI will either fail to find a relevant passage or retrieve a passage that answers a different question than the one the customer asked. The deflection rate will be low and the business will conclude, incorrectly, that AI support does not work for their product. The knowledge base requirements for AI resolution are specific and different from the requirements for a human-readable help centre. Articles need to be structured around single topics with clear, factual answers to the most common query variants. Long narrative articles must be split into shorter, focused pieces. FAQs need to be written so that the question in the article header closely matches the language customers use in their actual queries. Synonyms and regional spelling variants need to be accounted for. UK businesses that have invested in a help centre optimised for search engine discovery, not for AI retrieval, will find that the same content performs poorly as an AI knowledge source. Ignited Nepal audits the existing knowledge base against the AI retrieval requirements, restructures the content, identifies the gaps, and builds the additional articles needed before the AI is configured to begin resolution.

AI deflection rate and CSAT post-AI-resolution are not being tracked

The business case for AI customer support depends on one calculation: does the AI deflect enough queries, at sufficient quality, to justify the licence cost and the configuration investment. Most UK businesses that have deployed Intercom Fin or Zendesk AI cannot answer this question with data. The AI is running, queries are being processed, but no one has configured the reporting that would show what percentage of conversations the AI resolves without human involvement, what the CSAT score is for those AI-resolved conversations compared to human-resolved ones, and what the cost per ticket is before and after AI deployment. Without this measurement, the business is paying for an AI licence on the assumption that it is working, with no evidence to confirm or challenge that assumption. The absence of measurement also means the AI cannot be improved systematically. If the deflection rate is 30 percent and it should be 60 percent, the gap is almost always in the knowledge base: specific query types that the AI is not resolving because the relevant content is missing or poorly structured. Identifying those query types requires a deflection analysis that compares AI-resolved conversations to human-resolved ones and identifies the topic clusters where AI resolution is failing. This analysis cannot be done without measurement in place. Ignited Nepal configures Intercom's reporting, sets up CSAT surveys for AI-resolved and human-resolved conversations separately, builds a cost per ticket calculation model for the UK deployment, and delivers a monthly measurement report so the support manager has the data to demonstrate ROI to the business and to drive continuous improvement of the AI resolution rate.

What we engineer

What We Do

Ignited Nepal begins every UK AI customer support engagement with a GDPR compliance review specific to the AI vendor and the data processing involved. Before any AI feature is activated, we review the Data Processing Agreement the client has in place with Intercom, Zendesk, or the custom AI vendor, identify the gaps against UK GDPR Article 28 requirements, and work with the client's legal team or Data Protection Officer to complete the documentation. This includes reviewing the sub-processors used by the AI vendor's specific features, confirming that the UK IDTA or equivalent international transfer mechanism is in place for US-based processing, and documenting the legal basis for AI-processed personal data within the support context. The AI does not go live until the compliance documentation is complete.

For FCA-regulated clients, we conduct a Consumer Duty review of the AI support configuration before deployment. This review covers the disclosure language that informs retail clients they are interacting with an AI, the escalation triggers that route complex or sensitive financial queries to human advisers, and the response quality review process that monitors AI outputs against Consumer Duty standards on an ongoing basis. We configure the escalation path so that queries involving product suitability, complaint expressions, or regulatory topics are automatically routed to a human agent. We also design the monitoring framework that allows compliance teams to review AI-handled client communications against the Consumer Duty standard.

The knowledge base build is the technical core of every deployment. We audit the existing help centre content against Intercom Fin's retrieval requirements, restructure articles that are too long or too broad for AI resolution, and identify the query clusters where content is missing. UK-specific content includes GDPR-related customer rights queries (Subject Access Requests, right to erasure, data portability), Consumer Duty-related product queries for financial services clients, and VAT and statutory consumer rights content for e-commerce and retail clients. We write the articles the AI needs to achieve a target deflection rate that is agreed before the engagement begins.

Once the knowledge base is built to the required standard, we configure Intercom Fin or Zendesk AI to the resolution threshold appropriate for the client's support context. For businesses where accuracy is critical, such as financial services or healthcare, the resolution threshold is set conservatively so that the AI passes queries to a human agent whenever confidence is below a defined level. For e-commerce clients handling high volumes of transactional queries, the threshold can be set more aggressively. We configure sentiment detection so that customer expressions of frustration, urgency, or distress trigger human escalation regardless of the query topic.

Human escalation design is treated as a distinct workstream in every engagement. The handoff from AI to human agent must be clean: the human agent receives the full conversation history, the AI's attempted resolution, and the reason for escalation clearly summarised. We design the escalation messages so they are written in the brand's voice, configure SLA triggers so that escalated conversations are prioritised correctly in the agent inbox, and build the escalation categories that allow the support manager to track which query types the AI cannot yet resolve.

Deflection rate and CSAT measurement are configured from day one of deployment. We set up Intercom's reporting views to show AI resolution rate, human escalation rate, and CSAT by resolution type. We configure post-resolution CSAT surveys separately for AI-handled and human-handled conversations so the comparison is available. We build a cost per ticket calculation that applies the client's support team costs against the deflection data, producing a monthly ROI figure that connects the AI licence cost to the support efficiency outcome. For UK businesses with Intercom Fin, we configure the Fin Insights reporting to surface the query topics where resolution is lowest and direct the knowledge base improvement effort toward those gaps.

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What changes

What Changes

Before
After
Before UK GDPR Article 28 requires that a written Data Processing Agreement exists between the data controller (the business) and any data processor (the AI vendor) before personal data processing begins. This is not a recommendation or a best practice. It is a legal requirement, and the ICO has the power to issue enforcement notices and financial penalties where it is not met. When a business uses Intercom Fin or Zendesk AI to handle customer support queries, the AI vendor is processing personal data contained in those tickets. Name, email address, account details, and the content of the customer's enquiry are all personal data under the UK GDPR definition. The absence of a DPA means that processing is occurring without the documented legal basis the law requires. The complication for UK businesses is that both Intercom and Zendesk are US-headquartered companies. Their standard terms of service include Data Processing Addenda, but these documents are frequently signed without review, and they do not always address the specific AI features that have been activated. The AI features in Intercom Fin and Zendesk AI may involve data being processed by third-party AI models, including OpenAI or other large language model providers, that are not explicitly named in the DPA the business has signed. UK GDPR requires that sub-processors are identified and that the controller has approved their use. For cross-border transfers from the UK to the US, the UK International Data Transfer Agreement (IDTA) or the addendum to the EU standard contractual clauses must be in place. Most UK businesses using Intercom or Zendesk AI have not verified that their specific DPA covers the AI processing, the sub-processors involved in that processing, or the international transfer mechanisms that apply. The risk is that the AI is processing personal data right now on a legal basis that would not withstand ICO scrutiny.
After AI resolves 40 to 70 percent of Tier 1 customer queries without human involvement, reducing the volume of tickets that reach your support team.
Before The FCA Consumer Duty, which came into full effect for open products and services in July 2023, requires that all client communications deliver good outcomes for retail customers. This requirement applies to every touchpoint in the client relationship, including automated ones. When an AI agent responds to a retail client's enquiry about their insurance policy, their mortgage options, or their investment account, that response is a client communication subject to the Consumer Duty standard. The Duty requires that the communication is clear, that it does not mislead, that it is appropriate to the client's needs, and that it supports good decision-making. An AI that is not configured with these requirements in mind is generating client communications that may fail the Consumer Duty test on each of these dimensions. The specific Consumer Duty failures that AI support deployments commonly produce include: responses that describe a financial product in terms that are accurate but not understandable to a retail client; responses that fail to recommend escalation to a human adviser when the complexity of the query warrants it; and responses that do not disclose that the client is interacting with an AI. The FCA's Consumer Duty guidance makes clear that firms must monitor outcomes and take action where they identify that communications are not delivering the standard the Duty requires. For a firm whose AI is handling hundreds of client enquiries per week, the absence of a Consumer Duty review of that AI's configuration is a significant gap. The monitoring obligation requires that the firm knows what the AI is saying and that it has assessed whether those responses meet the Duty's standards.
After GDPR Data Processing Agreements with AI vendors are in place and documented before any customer personal data is processed by the AI.
Before The single most common reason that Intercom Fin achieves low deflection rates in UK deployments is that the knowledge base it draws on is either empty, sparsely populated, or structured for human reading rather than AI retrieval. Intercom Fin and Zendesk AI are retrieval-augmented generation systems. Their ability to resolve a customer query accurately depends entirely on the quality and coverage of the knowledge base they have access to. If the knowledge base has ten articles that are each 2,000 words long and structured as narrative prose, the AI will either fail to find a relevant passage or retrieve a passage that answers a different question than the one the customer asked. The deflection rate will be low and the business will conclude, incorrectly, that AI support does not work for their product. The knowledge base requirements for AI resolution are specific and different from the requirements for a human-readable help centre. Articles need to be structured around single topics with clear, factual answers to the most common query variants. Long narrative articles must be split into shorter, focused pieces. FAQs need to be written so that the question in the article header closely matches the language customers use in their actual queries. Synonyms and regional spelling variants need to be accounted for. UK businesses that have invested in a help centre optimised for search engine discovery, not for AI retrieval, will find that the same content performs poorly as an AI knowledge source. Ignited Nepal audits the existing knowledge base against the AI retrieval requirements, restructures the content, identifies the gaps, and builds the additional articles needed before the AI is configured to begin resolution.
After FCA Consumer Duty disclosures and human escalation triggers are configured, giving regulated businesses an auditable record of AI-handled client communications.
Before The business case for AI customer support depends on one calculation: does the AI deflect enough queries, at sufficient quality, to justify the licence cost and the configuration investment. Most UK businesses that have deployed Intercom Fin or Zendesk AI cannot answer this question with data. The AI is running, queries are being processed, but no one has configured the reporting that would show what percentage of conversations the AI resolves without human involvement, what the CSAT score is for those AI-resolved conversations compared to human-resolved ones, and what the cost per ticket is before and after AI deployment. Without this measurement, the business is paying for an AI licence on the assumption that it is working, with no evidence to confirm or challenge that assumption. The absence of measurement also means the AI cannot be improved systematically. If the deflection rate is 30 percent and it should be 60 percent, the gap is almost always in the knowledge base: specific query types that the AI is not resolving because the relevant content is missing or poorly structured. Identifying those query types requires a deflection analysis that compares AI-resolved conversations to human-resolved ones and identifies the topic clusters where AI resolution is failing. This analysis cannot be done without measurement in place. Ignited Nepal configures Intercom's reporting, sets up CSAT surveys for AI-resolved and human-resolved conversations separately, builds a cost per ticket calculation model for the UK deployment, and delivers a monthly measurement report so the support manager has the data to demonstrate ROI to the business and to drive continuous improvement of the AI resolution rate.
After CSAT scores for AI-resolved conversations are measured and compared to human-resolved ones, so quality does not degrade as volume moves to AI.
How it works

Process

  1. 01

    Compliance and configuration audit

    We begin by reviewing the existing AI support configuration, the Data Processing Agreements with AI vendors, and for FCA-regulated clients, the Consumer Duty documentation relevant to AI-handled client communications. The audit identifies the specific gaps that must be addressed before the AI is activated or expanded. We produce a written compliance gap report that is shared with the client's legal or compliance team before any configuration work begins.

  2. 02

    Knowledge base audit and content plan

    We audit the existing help centre content against the retrieval requirements of the AI platform being used. Every existing article is assessed for structure, topic scope, and relevance to the query types the AI needs to resolve. The output is a content plan that identifies which articles need to be restructured, which need to be split into smaller focused pieces, and which query topics require new articles to be written. The content plan includes estimated word counts and a prioritisation by query volume.

  3. 03

    Knowledge base build

    We write the knowledge base articles identified in the content plan. For UK deployments, this includes UK-specific regulatory content (GDPR customer rights, Consumer Duty disclosures for financial services clients, statutory consumer rights for e-commerce), product-specific content written against the client's actual support ticket history, and process articles covering the most common procedural queries. Articles are written to Intercom Fin's retrieval standards, not to search engine optimisation standards.

  4. 04

    AI configuration and escalation design

    We configure the AI platform with the knowledge base content, set the resolution threshold, and design the human escalation workflow. Escalation triggers are configured for sentiment signals, regulatory query types, and query complexity. The handoff message from AI to human agent is written in the client's brand voice and includes the conversation summary the agent needs to continue without asking the customer to repeat themselves. For FCA clients, Consumer Duty disclosures are built into the AI conversation flow.

  5. 05

    GDPR and regulatory documentation

    We complete the GDPR Data Processing Agreement review with the client's legal team or DPO, confirm the international transfer mechanisms for US-based AI vendors, and document the sub-processors involved in the AI features in use. For FCA clients, we produce the Consumer Duty configuration record that documents the AI disclosure language, the escalation triggers, and the monitoring process. This documentation is delivered before the AI goes live.

  6. 06

    Measurement setup and go-live

    We configure the deflection rate reporting, CSAT survey setup, and cost per ticket calculation before the AI is activated. The measurement framework is live from day one so that the first week of data is available for review. We conduct a go-live review at day 7 to assess initial deflection rates and identify any query types where the AI is not resolving correctly, then make knowledge base adjustments based on that data. Monthly reporting is delivered for the first three months, with a formal review at month three to assess whether the target deflection rate has been achieved.

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Common questions

Frequently asked questions about AI Customer Support Agent

What GDPR Data Processing Agreement is required when using Intercom or Zendesk AI to handle UK customer support queries?

UK GDPR Article 28 requires a written Data Processing Agreement with any vendor that processes personal data on your behalf, and this requirement applies to AI support vendors including Intercom and Zendesk. The DPA must specify the subject matter, duration, nature, and purpose of the processing, the type of personal data and categories of data subjects, and the obligations and rights of the controller. For Intercom and Zendesk, both companies provide Data Processing Addenda that can be executed as part of your account. However, the DPA must also address the sub-processors used by the specific AI features you have activated, including any large language model providers involved in AI response generation. If those sub-processors are processing UK customer data in the United States, the UK International Data Transfer Agreement or an equivalent mechanism must be in place to cover the cross-border transfer. Signing the standard Intercom or Zendesk DPA without reviewing it for AI-specific processing and sub-processor coverage leaves a compliance gap that the ICO could identify in an audit.

What FCA Consumer Duty requirements apply to AI-handled client support for UK financial services businesses?

The FCA Consumer Duty requires that AI-handled client communications for retail customers meet the same standards of clarity, fairness, and suitability as human-handled ones. FCA-regulated businesses deploying AI customer support must ensure that the AI discloses to the client that they are interacting with an automated system, that the AI's responses about financial products are accurate and not misleading, that the AI escalates to a human adviser when the complexity or sensitivity of the query warrants it, and that the business maintains oversight of AI-handled communications as part of its Consumer Duty monitoring framework. The specific implementation depends on the nature of the financial service, the query types the AI is handling, and the client type. IFAs handling retail investment clients face stricter requirements than a general insurance firm handling administrative queries. A Consumer Duty review of the AI configuration, completed before deployment, is the appropriate starting point for any FCA-regulated business.

How do I configure Intercom Fin to handle UK customer queries with a GDPR-compliant knowledge base?

Configuring Intercom Fin for GDPR compliance involves both the Data Processing Agreement with Intercom and the content of the knowledge base itself. The knowledge base should not contain personal data about individual customers. It should contain factual, policy-based, and process-based content that allows Fin to answer queries without needing to retrieve or present personal data. For UK businesses, the knowledge base should include articles covering the GDPR rights that customers frequently enquire about, including Subject Access Requests, the right to erasure, and data portability, with clear guidance on how customers can exercise those rights. The Fin configuration should also include escalation rules for queries that require access to personal data, routing those queries to a human agent who can access the customer record through secure, appropriate channels rather than having the AI attempt to process personal account information.

What ICO guidance should a UK business follow when deploying AI in customer support?

The ICO has published guidance on explaining decisions made with AI and on the use of AI in data processing contexts. The most relevant ICO guidance for AI customer support deployments covers the transparency obligation: businesses must inform customers when they are interacting with an AI system and must provide clear information about how the AI processes their data. The ICO guidance also addresses the accuracy principle, requiring that AI systems are designed and monitored to provide accurate information. For customer support, this means the knowledge base must be accurate and current, and the business must have a process for identifying and correcting AI responses that contain inaccurate information. The ICO guidance on automated decision-making under Article 22 may also apply if the AI support agent is making decisions that have a significant effect on customers, such as routing a complaint in a way that affects its outcome. The ICO guidance documents are publicly available at ico.org.uk and should be reviewed by the DPO before AI support deployment.

How do I measure whether Intercom Fin or Zendesk AI is delivering a positive return on investment for a UK business?

The return on investment for Intercom Fin or Zendesk AI is measured through three primary metrics: deflection rate, CSAT for AI-resolved conversations, and cost per ticket before and after deployment. Deflection rate is the percentage of conversations that the AI resolves without human involvement. A well-configured Intercom Fin deployment for a UK business with a complete knowledge base typically achieves a deflection rate between 40 and 65 percent for Tier 1 query types. CSAT for AI-resolved conversations measures whether the quality of resolution meets the customer's expectation. Cost per ticket is calculated by dividing your total monthly support cost by the number of tickets handled, with the AI reducing this figure by handling a proportion of tickets at near-zero marginal cost. Intercom provides Fin Insights reporting that shows deflection rate by query topic. Zendesk provides similar reporting through its AI analytics module. These reports, combined with a monthly cost per ticket calculation, give you the data to confirm whether the licence investment is justified.

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Deploy AI customer support with the GDPR compliance framework, FCA configuration, and deflection rate measurement built in from day one

UK businesses that have deployed Intercom Fin or Zendesk AI without completing the GDPR Data Processing Agreement review, the FCA Consumer Duty configuration for regulated clients, or the measurement setup are running compliance exposure and missing performance data simultaneously. Both problems are addressable, and neither requires a full re-deployment. In most cases, the AI platform is already in place and the work required is compliance documentation, knowledge base improvement, and measurement configuration. Ignited Nepal completes this work in a structured engagement that begins with the compliance audit and ends with a measurement framework that reports deflection rate, CSAT, and cost per ticket from week one. The engagement is scoped to the specific gaps the audit identifies, so you are not paying for configuration work that has already been done correctly. If you have Intercom Fin and it is achieving a 20 percent deflection rate, we will identify why and address it. If you have Zendesk AI and the Consumer Duty documentation is missing, we will complete it. The starting point is a diagnostic that assesses where you are and what specifically needs to be done.

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