AI systems built on your real data, not a chatbot wrapper
We connect AI lead scoring, voice agents and WhatsApp automation directly into the CRM, ad accounts and booking systems you already run — no platform migration required.
18ms
Campaign latency
99.98%
Uptime SLA
240ms
AI voice latency
The Problem
Most AI pilots never reach measurable impact
It’s easy to wire up a chatbot demo. It’s much harder to build something that actually survives contact with real customers, messy CRM data, and a sales team that won’t change its workflow overnight. Most "AI projects" stall at the prototype stage because they were built around a generic API call instead of the specific data and process a business actually runs on.
We build the less glamorous part first — the integration into your CRM, your ad accounts, your WhatsApp Business number — so the AI layer on top has something real to work with.
Service Breakdown
Our full-lifecycle AI automation services
Lead Intelligence
AI Lead Scoring & Qualification
- Score and prioritise every inbound lead automatically.
- Route hot leads to the right rep in seconds.
- Cut manual triage out of your sales pipeline.
Voice Automation
AI Voice Agents
- Industry-trained callers that follow up in under 240ms.
- Handle free-trial bookings and appointment confirmations.
- Log every call outcome straight into your CRM.
Messaging
WhatsApp AI Automation
- Automated broadcast and follow-up sequences.
- Two-way conversations handled without a human in the loop.
- Every reply logged and scored for intent.
Data Pipelines
CRM & Ads Integration
- Pull leads directly from JustDial, Facebook and Google Ads.
- Zero manual entry between ad platforms and your CRM.
- Deduplicate and merge leads across every channel automatically.
Deep Engineering
Generative AI Development
- Build context-aware generative features into your product.
- Work with API-based or open-source models depending on your budget.
- Keep ongoing token costs under control with smart prompt design.
Autonomous Systems
Agentic AI Development
- Deploy multi-step agents that handle real operational tasks.
- Automate decisions that used to need a person in the loop.
- Connect agents directly to the systems you already run.
Knowledge Access
RAG & Knowledge Retrieval
- Ground answers in your own documents and data, not the open web.
- Reduce hallucinated responses by retrieving real records first.
- Make internal knowledge searchable in plain language.
Custom Tuning
LLM Fine-Tuning
- Adapt a model to your specific terminology and use case.
- Keep your training data private and under your control.
- Build a smaller, cheaper model focused on one job.
Safe Integration
AI Model Deployment
- Package and deploy models securely into your own cloud.
- Monitor real-world performance once it’s live, not just in testing.
- Keep the system stable as usage grows.
Strategic Roadmap
AI Consulting Services
- Identify which of your workflows are actually worth automating.
- Audit whether your existing data can support the AI you want.
- Get a realistic roadmap and budget before committing to a build.
Process Engineering
AI Workflow Automation
- Replace slow, error-prone manual routines with automated pipelines.
- Connect scattered tools into one consistent process.
- Standardise how work moves between your team and your systems.
Scale Optimization
AI Automation Services
- Embed automation into legacy software you already run.
- Scale processing as your business grows without a full rebuild.
- Keep continuous monitoring on every automated process.
Operations
Workflow & Employee Automation
- Automate repetitive admin work off your team’s plate.
- Desktop monitoring and activity intelligence for remote teams.
- GPS check-in/out and field-team automation.
Migration
Static → AI Era Migration
- Upgrade static legacy sites into self-learning applications.
- Add AI chat, voice and automation to systems you already run.
- Migrate without downtime or losing existing SEO equity.
Technology Stack
Production-Ready Tools Powering Real AI Systems
We build automation using secure, production-proven tools we actually run in client projects — not a wishlist stack.
Industries Served
Built for high-intent verticals
Travel Agencies
Route bookings, quote generation, and AI follow-up sequencing for high-velocity enquiry volumes.
Real Estate
Lead qualification, property tour trackers, and AI follow-up agents for brokerages managing multiple listings.
Healthcare
Patient routing, appointment scheduling agents, and multi-branch coordination flows.
Fitness & Wellness
Free trial automation, class booking integration, and WhatsApp dispatch across branches.
Engagement Models
Partnership frameworks built to scale with you
01 · Predictable Monthly Retainer
Dedicated AI Engineering Pod
A senior engineer embeds directly into your workflow, handling continuous automation builds, model integration and ongoing iteration.
Deploy a dedicated pod02 · Sprint-Based Billing
Agile Build Scaling
Flexible capacity for fluid scopes — scale engineering time up or down tied strictly to your actual weekly sprint requirements.
Start agile scoping03 · Scope-Locked Pricing
Milestone-Based Delivery
Best for a discrete automation build — delivered within a fixed timeline and budget, with clear acceptance criteria at each milestone.
Estimate your projectWhy BPThink
What separates production systems from demos
Your data stays yours
Every automation we build runs on your infrastructure and your accounts — no black-box platform lock-in.
Built for ROI, not demos
We validate that a workflow is worth automating before we build it — not every process needs AI.
Works with what you already run
We integrate with your existing CRM, ad accounts and booking systems instead of replacing them.
Shipped, not just scoped
Every engagement ends in a live system in production — not a strategy deck.
Delivery Process
From data audit to production system
Workflow & Data Audit
We map your current process end-to-end and confirm the data you have is clean enough to automate reliably.
Feasibility & Cost Modelling
We estimate real API and infrastructure costs upfront, so there are no surprise bills once the system is live.
Sandbox Prototype
A working prototype is built first, so you can see the automation in action before full build-out begins.
Integration Build
We connect your CRM, ad accounts, WhatsApp Business API and any other systems the workflow depends on.
Testing Against Real Data
The system is tested against your actual historical data, not curated demo data.
Production Deployment
We deploy into your live environment and monitor closely through the first weeks of real usage.
Ongoing Monitoring
We track performance and tune the system as your business and data evolve.
FAQ
Questions we hear most often
Who owns the automation and code once it’s built?
You do, fully. Every workflow, integration and piece of code we build is deployed into your own infrastructure and accounts — there’s no ongoing dependency on BPThink to keep it running.
How long does a typical AI automation project take?
Most single-workflow builds (like a lead scoring pipeline or WhatsApp automation) take 2–6 weeks. Larger multi-system integrations can run 8–12 weeks depending on scope.
Do we need a large budget for AI infrastructure?
No. Most of what we build runs on pay-per-use AI APIs (OpenAI, Gemini, Claude) rather than dedicated GPU infrastructure, so costs scale with your actual usage, not a fixed overhead.
Can this integrate with our existing CRM or booking system?
Yes — we specialise in connecting AI automation to systems you already run, like Mindbody, JustDial, Meta Ads, or your own CRM, rather than asking you to migrate everything to a new platform.
What if our data is messy or scattered across multiple tools?
That’s the starting point of our process — the first step of every engagement is a workflow and data audit before any automation gets built.
How do you measure whether the automation is actually working?
We agree on concrete metrics upfront — response time, conversion lift, hours saved — and track them from the day the system goes live.
What happens if the AI gives a wrong or unexpected response?
Every automation we build includes guardrails and human-in-the-loop checkpoints for anything customer-facing or high-stakes, so a bad output gets caught before it reaches a customer.
Guide
A practical guide to AI automation
What does AI automation actually mean for a small or mid-sized business?
For most businesses, AI automation isn’t about building a custom large language model — it’s about wiring existing AI APIs into the workflows you already run: scoring leads as they come in, following up on WhatsApp without a human typing every message, or routing a call to the right voice agent. The value comes from removing manual, repetitive steps between your ad platforms, your CRM and your customer — not from the sophistication of the model itself.
When is it worth investing in AI automation?
The clearest signal is a repetitive, high-volume manual task that’s costing your team hours every week — responding to leads, confirming bookings, or re-entering data between two systems that don’t talk to each other. If a task happens dozens of times a day and follows a predictable pattern, it’s usually a strong automation candidate. If it’s a one-off or requires real judgment every time, a simpler tool or process change is often the better answer.
How should you evaluate an AI automation partner?
Ask for examples of systems that are actually running in production, not just prototypes — and ask what happens to the data and code once the engagement ends. A partner who tells you when AI isn’t the right fit for a particular workflow is generally more trustworthy than one who says yes to everything.
What actually drives the cost of an AI automation project?
Three things matter most: how many systems the workflow needs to connect to, how clean your existing data is, and whether the automation is customer-facing (which usually needs more guardrails and testing). A single WhatsApp follow-up automation is a fraction of the cost of a multi-system lead-routing pipeline with voice, CRM and ad platform integration all connected together.
Common mistakes businesses make with AI automation
The most common one is starting with the tool instead of the problem — deciding "we need a chatbot" before defining what metric it’s supposed to move. Close behind that is skipping a proper look at existing data before building, and treating automation as a one-time project rather than something that needs occasional tuning as your business changes.