Synapserve Talk to a specialist

AI agent and chatbot development

An AI agent development company for agents that answer correctly and act safely

Synapserve is an AI agent development company that builds customer support chatbots, internal knowledge assistants and agents that work inside your ERP and CRM. Every agent is grounded in your own data, tested against your real questions before launch and designed to hand over to a person when it is not sure.

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The problems we're brought in to fix

The demo worked. Real customers broke it.

A chatbot that impresses in a meeting can still invent a refund policy, quote last year's price or promise a delivery date nobody agreed. Fluent answers are easy; correct ones take engineering. Before you hire an AI agent development company, ask to see how it measures wrong answers, not just how natural the answers sound.

Your knowledge is scattered and out of date

Policies sit in SharePoint, product details in PDFs, pricing in the ERP and the real answers in the heads of a few senior people. An assistant that searches all of it without respecting who is allowed to see what does not save time. It creates a new route for confidential data to leak.

Staff still retype documents into the ERP

Invoices, purchase orders and delivery notes arrive as PDFs and email attachments in every layout imaginable. Someone keys them into Business Central or Dynamics 365 by hand, mistakes reach the ledger, and month-end turns into a hunt for mismatched quantities and prices.

Nobody owns the agent after go-live

Models are updated, documents change and customers ask questions nobody anticipated. Without logging, monitoring and a regular review of failed conversations, quality drifts quietly until a complaint or a wrong commitment makes it visible.

What we deliver

Customer support agents on web, WhatsApp and email

Agents that answer from your help content, order data and policies, look up order status, open or update tickets in your helpdesk or CRM, and pass the conversation to a person with the full history when needed. On WhatsApp we work within the WhatsApp Business Platform rules, including approved message templates for anything sent outside the customer service window.

Internal knowledge assistants grounded in your documents

Retrieval-based assistants that search SharePoint, file shares, wikis and other approved sources, answer with citations to the exact passage they used, and only retrieve documents the person asking is already allowed to open. When the sources do not contain the answer, the assistant says so instead of guessing.

Agents that take actions in ERP and CRM

Agents that check stock, draft sales quotes, prepare purchase orders or update customer records in Business Central, Dynamics 365 and other systems through their APIs, using a service account with only the permissions the task needs. Anything that changes money, stock or customer commitments waits for a named person to approve it, and every action is logged.

Document processing for invoices and purchase orders

Extraction of header and line data from supplier invoices, customer purchase orders and delivery notes, validated against vendor records, open orders and receipts before anything is posted. Fields with low confidence and lines that fail the match go to a review queue rather than straight into the ledger.

Evaluation suites and guardrails

A test set built from your real questions, edge cases and misuse attempts, scored for accuracy, citation quality and correct refusals on every change to prompts, models or data. Guardrails cover topic limits, prompt injection through documents or messages, personal data redaction, tone and the actions an agent may never take.

Monitoring and continuous improvement

Dashboards for answer quality, hand-off rate, unanswered questions, latency and cost per conversation, with conversation logs your team can review. A regular review of failures feeds missing content and new test cases back into the system so the agent improves on evidence.

How a project runs

Every step has an owner on your side and on ours, and nothing moves forward without your sign-off.

  1. Choose the use case and define a correct answer

    We start with one workflow where both the value and the risk are clear, and agree with your team what a correct, an acceptable and an unacceptable answer looks like. That definition becomes the acceptance standard for the rest of the project.

  2. Audit the data and access rules

    We map every source the agent will use, who owns it, how current it is and who is allowed to see it. Contradictions and gaps in your content are cheaper to fix now than after customers find them.

  3. Build the test set before the agent

    We collect real questions from tickets, emails and staff, add awkward edge cases and attempts to misuse the agent, and write the expected outcome for each. The agent is built and judged against this set, not against impressions from a demo.

  4. Build, ground and connect

    We design retrieval, prompts, tools and approval steps, choose a model that fits your accuracy, speed, cost and data-residency needs, and connect the agent to your helpdesk, ERP or CRM through their APIs with least-privilege access.

  5. Pilot with people in the loop

    A limited release to internal users or a slice of customers, with every answer reviewable and an easy route to a person. We tune on what the pilot shows and widen access only when the test results and the pilot both meet the agreed standard.

  6. Run, monitor and improve

    After launch we track quality and cost, review failed conversations, keep the test set current and handle model upgrades, so every change is tested before it reaches your customers or staff.

Ways to work with us

Proof of value

A fixed-scope build on one use case, using your real data and a test set agreed with your team, ending in a written evaluation report so you decide on evidence whether to go further.

Build and launch

Full delivery of a production agent, including integrations, guardrails, approval flows, a security and privacy review, and handover documentation your team can maintain.

Managed agent operations

Ongoing monitoring, content updates, test-set maintenance and model upgrades by people who know your agent, provided as a support arrangement or as part of a dedicated team.

Delivered from India, in your working hours:

Questions we're often asked

How do you stop an AI agent from making things up?

We combine several controls rather than relying on one. The agent answers only from retrieved sources and cites them, it is instructed and tested to say it does not know when the sources are silent, and a test set of real questions runs on every change. Sensitive topics, low-confidence answers and frustrated customers are routed to a person.

What should we look for in an AI agent development company?

Ask how accuracy is measured before launch, what happens when the agent is unsure, how permissions on internal documents are enforced and who monitors the agent after go-live. A team that cannot show you an evaluation method and its results is asking you to trust a demo.

Can an agent post transactions in Business Central or Dynamics 365 on its own?

Technically it can, but we design for human approval by default. The agent prepares the quote, order or journal and a named person approves it. Fully automatic actions are switched on only for low-risk, well-tested cases you choose, and every action is logged. Microsoft is also adding Copilot features and agents to Business Central and Dynamics 365, and we will tell you when a built-in option fits better than a custom build.

Where does our data go, and is it used to train models?

We use enterprise model services whose terms exclude your data from model training, and deploy in a region that matches your data-residency needs where the provider offers one. Personal data can be redacted before it reaches the model, and we document the data flows for your privacy review under the GDPR, UK GDPR or India's Digital Personal Data Protection Act, as relevant.

Which channels can a customer support agent work on?

Website chat, WhatsApp through the WhatsApp Business Platform, email and helpdesk tools are the most common. The same knowledge, rules and hand-off logic sit behind every channel, so customers get consistent answers wherever they ask.

Which AI models do you use?

We are not tied to one provider. We compare models from major providers, including options hosted on Microsoft Azure and open-weight models, on accuracy against your test set, speed, cost and where they can be hosted. Because the evaluation suite is in place, switching models later is a measured decision rather than a gamble.

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