CRM Implementation
HubSpot, Zoho or Pipedrive configured to how your team actually sells.
from ₱165,0003–5 wks
Add to quote →React Web Development Services AI Studio
AI that does the follow-up your team forgets.
Not a chatbot bolted onto a contact form. Agents that qualify, scope, quote and book — wired into your CRM, fenced in by guardrails, and honest about what they don't know.
reactph/advisor · engine v1 · deterministicservices scored ......... 95quote reproducibility ... 100%prices invented ......... 0cost per conversation ... ₱0.00 (guided mode)
Short answer
React Web Development Services builds AI sales agents and support chatbots from ₱185,000, custom retrieval-augmented generation over your own documents from ₱280,000, internal operations automation from ₱140,000, Messenger and WhatsApp commerce from ₱95,000, and runs AI-search visibility (AEO/GEO) programmes from ₱42,000/mo. Based in Porac, Pampanga, Philippines.
How we actually build it
The model handles language.Code handles the numbers.
Most AI agency work fails the same way: someone lets a language model quote prices, promise timelines or check availability, and it confidently invents an answer. Prompting alone will not fix that.
So we split the job. Anything that must be exact — pricing, stock, availability, eligibility — is computed by deterministic code. The model does what it's genuinely good at: understanding a messy question and explaining an answer in plain language.
The test we hold ourselves to
Ask the same question three times and a well-built agent gives the same commercially binding answer three times. If it doesn't, it isn't ready to talk to your customers.
Layer 01
Deterministic core
Scoring, pricing, eligibility and availability in ordinary, testable code. Same input, same output, every time — and unit-testable, which a prompt is not.
Layer 02
Language layer
Claude handles conversation, ambiguity and explanation, with a system prompt that pins every fact it's allowed to state and refuses everything else.
Layer 03
Graceful failure
API down, key missing, rate limit hit? The agent degrades to a local matcher and says so. It never fakes a result — software that lies about its state is worse than software that stops.
Capabilities
Eight ways we put AI to work.
Every one of these is a line item with a published price. No "AI transformation" engagements with a number you find out later.
Marketing Automation & Journeys
Lifecycle sequences that follow up faster than any human will.
from ₱95,0002–4 wks
Add to quote →AI Sales Agent / Support Chatbot
An agent like the one on this site — qualifies, scopes and books, 24/7.
from ₱185,0004–6 wks
Add to quote →AI Content Operations Enablement
Your team, tooled and trained to produce 5× without losing the voice.
from ₱120,0003–4 wks
Add to quote →Internal Operations Automation
Quotes, approvals, onboarding and reporting — the admin nobody should do by hand.
from ₱140,0003–5 wks
Add to quote →WhatsApp / Messenger Commerce
Sell in the inbox where Filipino customers already prefer to talk.
from ₱95,0002–4 wks
Add to quote →Custom AI Integration (RAG & Agents)
Your documents and data, made answerable. Built on Claude or your model of choice.
from ₱280,0006–10 wks
Add to quote →Sales Enablement Toolkit
Playbooks, sequences and collateral so every rep sells like your best one.
from ₱85,0002–3 wks
Add to quote →AEO / GEO
Your next customer may never see a search result.
They'll ask an assistant "who builds booking systems in Pampanga?" and act on the three names it says. If your business isn't legible to those systems, you're not in the running — and no amount of traditional ranking fixes it.
Answer Engine Optimisation is the discipline of being quotable: unambiguous factual content, structured data an assistant can parse, crawler access for AI bots, and a machine-readable summary of who you are. You will also see it called generative engine optimisation (GEO) or generative search optimisation (GSO) — same discipline, three labels, and we do all of it.
We practise this on ourselves
This site ships an llms.txt
A machine-readable summary of who React Web Development Services is, what we charge and what each page covers — at /llms.txt. Our robots.txt explicitly welcomes GPTBot, ClaudeBot, PerplexityBot and Google-Extended, because being cited is worth more to us than hoarding the content.
And structurally
Every page carries a schema graph
ProfessionalService with full service-area and payment data, BreadcrumbList, FAQPage on question content, Article on the guides, plus a published price on every service. Assistants quote what they can parse unambiguously.
The honest caveat
Nobody can guarantee a citation
AI answer selection is opaque and changes without notice. What we can do is remove every technical reason to be excluded, and measure prompt-level visibility monthly so you know where you stand. Anyone promising guaranteed AI rankings is selling you something they can't deliver.
Case study zero
The agent on this site, taken apart.
We have no client case studies yet, so here is the one thing we can show you in full detail — including the mistakes we had to fix.
PROBLEM
A quote engine that behaved like a shopping cart
The first version happily quoted a Shopify build and headless commerce to the same client. Three different websites, in one case. And ₱111,000 a month of retainers to a business with a ₱200,000 build budget. Every one of those is a lost deal and a damaged reputation.
FIX 01
Mutual exclusion families
Services are grouped into families where quoting two members is nonsense. Highest-scoring member wins, the rest are dropped. A second rule lets a bigger scope absorb a smaller one, so buying the premium 3D site doesn't also bill you for the 3D bolt-on module.
FIX 02
Budget caps with no tolerance
A hard ceiling on the build, a separate monthly ceiling tied to that build budget, and a maximum line count per band. The agent physically cannot present a number above what you told it.
FIX 03
Relevance gates, not just scores
A property developer was being offered Lazada and Shopee marketplace operations, purely because it scored well. Specialist retainers now have to match the client's actual industry or goal, not merely rank next.
FIX 04
Permission to recommend less
If you say you're just exploring, or don't know your budget, it stops selling and points you at a ₱25,000 paid discovery instead. If your existing site is underperforming it suggests a ₱35,000 audit rather than a rebuild. That behaviour is deliberate — and it closes more work than the alternative.
RESULT
Reproducible, in-budget, internally consistent
Guided scoping runs entirely in your browser: no API call, no latency, no per-conversation cost, and identical answers for identical inputs. Free-text questions go to Claude with a system prompt that pins every price and treats your message as data, not instructions — so nobody can talk it into a discount.
Questions
The things clients actually ask.
More in the full FAQ, or ask the Advisor directly — it answers from the same facts.
For pricing, running costs and the cases where an agent is the wrong purchase, see the AI agents service page.
How much does an AI agent cost in the Philippines?
An AI sales or support agent starts at ₱185,000, covering conversation design, CRM integration and the guardrail set that stops it inventing prices or promises. A simpler Messenger or WhatsApp commerce build starts at ₱95,000. Custom retrieval over your own documents starts at ₱280,000. Running costs depend on volume and model choice — we size that with you before you commit, because an agent with a surprise monthly bill gets switched off.
Can you stop it making things up?
Not by prompting alone — anyone who tells you otherwise hasn't shipped one. The fix is architectural: anything commercially binding is computed in code, and the model is only allowed to explain. The Advisor on this site never generates a price; it reads one from a scoring engine.
We also test adversarially before launch — trying to talk the agent into discounts, false promises and disclosing its own instructions — and hand you the results.
Which model do you use?
Claude by default, because the safety behaviour and instruction-following suit customer-facing work. We're not religious about it: if your stack, data-residency rules or budget point elsewhere, we'll build on what fits and say why. The architecture matters far more than the model badge.
Where does our data go?
Only what's needed to answer the question. We don't send customer databases to a model provider. Retrieval systems fetch the specific document chunk relevant to a query rather than shipping your whole corpus, and we document the data flow so your DPO can sign it off under the Data Privacy Act (RA 10173).
Will this replace our staff?
In our experience it replaces the work nobody wanted: the 2am enquiry, the fifth follow-up, the copy-paste between systems. It's poor at judgement, negotiation and relationships — which is most of what your good people actually do. If a vendor's pitch is headcount reduction, ask them to guarantee it in the contract and watch what happens.