Email:info@softosmith.com
Working Hours:Mon - Fri: 9 AM - 5 PM (PKT)
We build conversational AI agents that answer real questions grounded in your own documentation, guide customers through your product, and reduce the volume hitting your support queue — deployed to chat, messaging, or helpdesk.
Most chatbots follow a scripted decision tree — the moment a question falls outside the flowchart, the customer hits a dead end, repeats themselves to a human, or gives up entirely.
Decision-tree bots that can't answer anything outside their preset options.
Answers pulled from a static FAQ list instead of your actual, current documentation.
Handoffs to a human that lose all conversation context, forcing the customer to start over.
A conversational AI agent is a chat-based system that retrieves answers from your actual documentation and data through RAG, holds multi-turn context, and can call your CRM or helpdesk to check or update information — not a scripted bot limited to a decision tree.
Everything needed to take support from a static FAQ to an agent that resolves real questions.
A chat widget on your site that answers real product and support questions instead of collecting an email and disappearing.
Agents deployed to WhatsApp, Messenger, or Slack, so customers get answers on the channel they already use.
Agents that resolve common questions before they become a ticket, and hand off cleanly with full context when they can't.
The same agent logic deployed consistently across web chat, messaging apps, and internal tools, not rebuilt per channel.
Answers pulled from your actual documentation, help center, and product data through retrieval, not the model's own guesswork.
When a conversation needs a person, the agent escalates with full context captured, instead of making the customer repeat themselves.
We orchestrate conversation flow through LangGraph or CrewAI, index your documentation and product data into a RAG pipeline so answers stay grounded, wire in tool-calling to your CRM or helpdesk so the agent can act, and apply guardrails and evaluation so it says "I don't know" instead of guessing.
Real conversational AI means working with actual retrieval and orchestration patterns, not a prompt pasted into a widget.
Multi-turn conversation flow managed through LangGraph or CrewAI, so the agent handles branching questions without losing track of context.
Vector search over your docs, help center, and product data on Pinecone, Qdrant, or pgvector, keeping answers grounded and current.
The agent calls into your CRM or helpdesk directly — checking an order, updating a ticket — instead of just describing what it would do.
Conversation memory so the agent remembers what was already said and doesn't ask the customer to repeat themselves.
Structured prompts and retrieval grounding that keep the agent from inventing answers when it doesn't actually know.
A clear, six-step process from discovery to ongoing support.
We review your support volume, common questions, and which channels the agent needs to cover.
Your docs, help center, and product data structured and indexed for retrieval.
Conversational flow, tool-calling, and guardrails built and tested against real questions.
Connected to your helpdesk or CRM and tested against real conversation transcripts.
Rolled out to your website or messaging channel, with escalation paths in place.
Ongoing tuning as new questions and edge cases come up.
Product support agents that answer feature and troubleshooting questions grounded in your docs.
Order status, returns, and product Q&A agents connected to your store data.
Intake agents that answer common questions and qualify a lead before a human joins the conversation.
Enrollment and course support agents connected to your LMS or CRM.
Patient-facing FAQ and intake agents built with compliance-aware handling of sensitive information.
Customers get an answer immediately, at any hour, instead of waiting on a queue.
Common questions get resolved without adding to your support team's ticket count.
The same accurate answer every time, grounded in your actual documentation.
Handles a spike in questions the same way it handles a quiet day, without adding headcount.
No client logos or star ratings here — just the commitments every agent build is held to.
You work directly with the engineer building your agent — no account managers relaying messages back and forth.
The quote we give you upfront is what you pay. No surprise invoices once development starts.
Softosmith is led by Amin Ali, Founder & Lead AI Engineer with 8+ years building automation and RAG pipelines, so your agent's retrieval logic is designed properly, not bolted together.
The agent's logic, prompts, and integrations are yours. Nothing rented or locked behind a proprietary platform after handover.
You know exactly where your build stands at every stage, from discovery through deployment — no radio silence.
A post-launch support window is built into every engagement, so tuning after real conversations start doesn't become your problem alone.
Fixed-scope pricing to start — final quotes depend on the channels and integrations involved. Need agents across many channels? Contact us for an Enterprise quote.
$2,000 starting
One conversational agent deployed to a single channel, like your website chat.
$6,000 starting
One agent deployed consistently across web chat, messaging, and helpdesk.
Straight answers to what clients usually ask before starting a build.
We build on OpenAI, Anthropic (Claude), Google Gemini, and open-source models where it fits the use case and budget — the model is chosen for the job, not tied to one vendor.
A simple chatbot follows a scripted decision tree. A conversational AI agent retrieves real answers from your documentation through RAG, can call your systems to check or update data, and handles questions that don't fit a predefined script.
Website chat widgets, WhatsApp, Messenger, Slack, and internal tools are all options. We scope the channels during discovery based on where your customers actually are.
Answers are grounded in your actual documentation and data through a RAG pipeline, with guardrails that push the agent to say it doesn't know rather than invent an answer.
Yes. When a conversation needs a person, the agent escalates with the full conversation context already captured, so your team isn't starting from zero.
You do. The conversation logic, prompts, and integration code are yours — nothing is locked behind a proprietary platform or an ongoing license with us.
A single-channel agent typically takes 2 to 3 weeks. A multi-channel deployment with several integrations usually runs 5 to 8 weeks.
Yes. Every engagement includes a post-launch support window for tuning as real conversations reveal new questions and edge cases.
See the full range of AI agent services we build, from conversational to voice to system integration.
Extend the same agent logic to phone calls for support and lead qualification.
Connect your conversational agent more deeply into your CRM and internal tools.
Tell us about your support channels and we'll scope an agent build around them.
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