AI Workflow Intelligence — San Francisco

Do more.
With less.
Ship real AI.

Tacpoint builds production AI systems for growing B2B teams — agentic workflows, data pipelines, private RAG deployments. No hype. No 18-month timelines. Measurable ROI or we don't pitch it.

200–400%typical ROI yr 1
6–9 wksavg. to production
100%source code yours
TRIGGER EVENT AI CLASSIFIER route by intent + context JUDGMENT? yes HUMAN LOOP no AUTO EXECUTION governed by policy rules OUTPUT + AUDIT LOG
Trusted by
VISACISCOSOFIELLETRANSPERFECTSBE
95%
of AI pilots fail to deliver P&L impact
MIT NANDA, 2025 — root cause: bad integration, not bad models
74%
of companies can't scale AI despite adopting it
Data quality and integration gaps — the bottleneck Tacpoint solves
70%
of companies say AI agents are their #1 automation lever
LangChain State of AI, 2025 — agentic workflows are the new baseline
67%
success rate when you partner vs. build solo
MIT, 2025 — internal builds succeed only 33% of the time
The Architect — on-site discovery

Describe a task.
Get a roadmap.

Tell The Architect about one workflow consuming your team's time. It analyzes the logic, identifies automation potential, and returns a structured implementation roadmap — before you talk to a human.

01
Describe one repetitive task consuming 5+ hours per week
02
Classify whether it's data movement or human judgment
03
Receive a problem statement, solution type, and logic diagram
04
Enter your email — a Tacpoint engineer reviews every roadmap before delivery
architect@tacpoint.ai — workflow discovery v2
tp>initializing workflow discovery module...
tp>connected. no hype. just logic.
What is one repetitive, manual task that consumes at least 5 hours of your team's week?
>
/ Services

Five services.
One goal: ROI.

Validated against real SMB demand. We implement systems that compress specific costs — not AI as a concept.

01 / Agentic Workflow Automation

Your team does the thinking. AI does the rest.

Multi-step AI agents that handle intake, triage, data routing, and document processing — with human-in-the-loop checkpoints at every decision requiring judgment. 30–40% cost reduction. 80% faster processing.

TRIGGER AI AGENT HUMAN GATE ORCHESTRATE OUT
Client intake, invoice processing, order triage
CRM sync, compliance reporting, lead routing
200–400% ROI typical within 12–24 months
02 / AI Data Readiness

Your data is holding your AI back. We fix that.

74% of companies can't scale AI because their data is siloed, dirty, or disconnected. We collect, clean, parse, merge, and structure your data into AI-ready pipelines — the prerequisite every other AI investment depends on.

CRM SHEETS PARSE CLEAN · MERGE AI-READY structured pipeline
Data consolidation across siloed systems
ETL pipelines, schema normalization, enrichment
10.3× AI ROI vs. 3.7× with poor data (MuleSoft)
03 / Private RAG Deployment

Ask your company's own knowledge. Privately.

Retrieval-augmented generation over your document library, contracts, SOPs, and CRM — deployed inside your VPC. Your data never leaves. Staff get instant, cited answers. Fastest ROI of any AI use case: 2–4 months to break-even.

YOUR VPC DOCS + SOPs VECTOR INDEX LLM CITED ANSWER
Legal, financial services, healthcare, logistics
87% reduction in research time (live case study)
Zero data egress — HIPAA/SOC2-compatible
04 / Natural Language BI

Your data answers back. No analyst required.

Text-to-SQL layer over your existing Postgres, Snowflake, or BigQuery warehouse. Any team member can ask "what were our top 10 accounts last quarter?" and get a structured, cited answer in under 10 seconds.

PLAIN ENGLISH Q TEXT → SQL AI layer INSTANT ANSWER cited + auditable
3 days → under 10 seconds (live case study)
Works with Postgres, Snowflake, BigQuery
100% self-serve — no SQL knowledge needed
05 / AI Transformation Strategy

A 2-week paid diagnostic. Then a scoped plan — or you walk away with the roadmap.

We map your operations, identify your 2–3 highest-ROI automation targets, and deliver a sequenced implementation plan with effort-vs-impact scores. No lock-in. You own the output. This is the right first step if you're not sure where to start — or if you've tried AI before and it didn't land.

WEEK 1–2
Discovery & mapping
Interview key team members, map current workflows, audit data state
DELIVERABLE
Automation roadmap
Prioritized list of AI opportunities with ROI estimates and architecture sketch
THEN
Your call
Proceed to implementation sprint or keep the roadmap. No pressure either way.
For teams that want to move but aren't sure where to start
For teams burned by AI projects that never shipped
Fixed fee, defined deliverables, 2 weeks maximum
AI ROI Estimator

How much is manual work actually costing you?

Most teams underestimate the cost of repetitive operations by 3–4×. This calculator surfaces the real number — including error correction overhead, context-switching tax, and opportunity cost.

Tacpoint implementations typically recover 60–80% of this figure in year one, with break-even between months 2 and 5.

What's included
Direct labor cost of manual tasks
Error correction overhead (avg 1.3× multiplier)
Context-switching cost
Opportunity cost — what those hours could generate
// roi_estimator.js — input your parameters
Hours/week on manual tasks20 hrs
Team members doing this work5 people
Avg fully-loaded hourly rate$65/hr
Annual cost of manual operations
$338K
direct labor before overhead
Direct labor$338,000
Error overhead (1.3×)$101,400
Estimated recoverable (70%)$307,580
// ai_readiness_scorer — 5 questions
How does your team handle repetitive data tasks today?
Fully manual — spreadsheets, email, copy-paste
Partially automated — some Zapier/Make flows
Mostly automated — dedicated ops stack
7
/ 10 AI READINESS SCORE
ProgressQuestion 1 of 5
AI Readiness Score

Know where you stand before you build.

Five questions. Scored on infrastructure maturity, data accessibility, team adoption readiness, compliance posture, and timeline urgency.

Scores route you to the right first step — not a one-size-fits-all booking link.

Score 1–4
Start with The Architect discovery flow
→
Score 5–7
Book a 30-minute strategy preview
→
Score 8–10
Proceed to paid diagnostic engagement
→
The problem we solve

Most AI projects fail before they ship.

The issue isn't the model. It's the integration. The data. The missing workflow logic. The team left to figure it out alone. Tacpoint is the implementation layer between AI's potential and your actual operations.

✗
Generic AI tools stall in real workflows
ChatGPT and Copilot are general-purpose. They don't learn your processes, your data, or your rules.
✗
Data is siloed, dirty, or disconnected
95% of IT leaders say integration is the #1 AI barrier. Clean data is the prerequisite no one talks about.
✗
Internal builds fail two-thirds of the time
MIT, 2025: partnering succeeds 67% of the time. Building solo: 33%. The skills gap is real and widening.
✓
Tacpoint closes the implementation gap
We build specific systems for specific workflows — with governed autonomy, defined deliverables, and measurable ROI targets before a single line of code is written.
$338K
avg. annual cost of manual ops for a 5-person team
Based on 20 hrs/week at $65/hr. Run your own numbers with the calculator above.
6–9 mo.
average payback period for a Tacpoint implementation
Most clients reach break-even before the implementation sprint ends.
100%
source code ownership — you keep everything we build
No vendor lock-in. No ongoing licensing on the systems we build for you.
2 wks
from kickoff to actionable automation roadmap
Paid diagnostic. Fixed deliverable. No 18-month enterprise timelines.
91%
of AI-using SMBs report higher revenue after adoption
U.S. Chamber of Commerce, 2025. The gap between users and non-users is widening fast.
READY?
Find out if your workflows are ready for AI in 5 questions.
FAQ

Common questions.

We build systems that work in your environment, with your data, under your governance rules. Most questions reduce to: how much control do I keep?

The answer is: all of it.

Do I need to move my data to use your AI systems? +
No. Every system we build runs inside your existing environment — on-premise, private cloud, or VPC. Your data never touches a shared AI API unless you explicitly choose that architecture and understand the tradeoffs. We default to private deployment.
How is Tacpoint different from just using ChatGPT or Copilot? +
Generic AI tools are general-purpose. We build systems specific to your workflow, your data, and your rules — with governed autonomy built in. The difference is between a power tool and a production line built for your exact product.
What does a typical engagement look like? +
We start with a paid diagnostic — 2-week discovery and architecture phase. Then a defined implementation sprint (6–12 weeks), followed by handoff and a support period. We provide full source code. You own everything we build.
We're not very technical. Can you still work with us? +
Yes. Our discovery process doesn't require technical depth on your end — we map the workflow and handle all implementation. What we need is your process knowledge: how work actually moves through your organization. You know that better than we do.
What size companies do you work with? +
Primarily SMBs with 10–500 employees in professional services, healthcare operations, financial services, and logistics. We're built for companies that can't absorb 18-month enterprise implementations.
Will AI replace my team? +
Our systems compress labor — they don't replace judgment. We build with human-in-the-loop architecture at every decision gate requiring context, compliance, or nuance. AI handles the repetitive volume; your team handles the exceptions.
My data is a mess. Can you still help? +
That's exactly where we start. Most of our engagements begin with a data readiness phase — consolidating siloed sources, cleaning schemas, building pipelines. This is the work that determines whether an AI project succeeds or becomes another failed pilot. A messy data state isn't disqualifying; it's the job description.
We've tried AI tools before and they didn't stick. What's different? +
Generic tools stall because they don't know your processes. We build systems specific to your workflow, your data format, and your decision logic — not off-the-shelf products you have to contort your business around. The MIT research is clear: 95% of AI pilots fail due to integration failures, not model quality. We fix the integration layer.