RLM ROI Analysis & Customer Messaging
Sales Enablement Guide
Version: 1.0
Date: January 13, 2026
Table of Contents
- Value Proposition Framework
- ROI Calculator
- Customer Case Studies
- Sales Talk Tracks
- Objection Handling
- Marketing Materials
Value Proposition Framework
The CODITECT Transformation Story
BEFORE CODITECT
├─ Manual repetitive work consumes 60-90% of time
├─ AI tools limited by 128K token context windows
├─ Critical details lost in summarization
├─ Complex tasks require expensive specialists
└─ ROI unclear and hard to measure
AFTER CODITECT + RLM
├─ 60-90% of work automated
├─ Unlimited context processing (10M+ tokens)
├─ 95%+ accuracy with zero information loss
├─ Complex analysis in minutes, not days
└─ Proven 342x ROI on analysis tasks
Core Value Pillars
Pillar 1: Unlimited Intelligence
The Problem:
"Our contracts are 500 pages. AI summaries miss critical clauses that cost us $500K in unexpected liabilities."
CODITECT Solution:
"Process unlimited document lengths with 95%+ accuracy. Analyze every clause, cross-reference every term, extract every risk. Zero information loss."
Proof Point:
- Processes 10M+ tokens (vs. 128K industry standard)
- Validated on MIT research benchmarks
- Customer results: 500-page contracts analyzed in 2 minutes
Pillar 2: Quantifiable ROI
The Problem:
"We spent $100K on AI tools last year. Can't prove if we saved any time."
CODITECT Solution:
"Every task shows exact time saved and cost. Average 342x ROI on complex analysis. 20x ROI overall in 20 days."
Proof Point:
- Real-time ROI dashboard
- Per-task time and cost tracking
- Customer validation: $478K annual savings (legal firm)
Pillar 3: Enterprise-Grade Automation
The Problem:
"AI chatbots are toys. We need production systems that integrate with our workflows."
CODITECT Solution:
"Complete automation platform with 13 specialized skills, workflow orchestration, multi-agent collaboration, and enterprise security."
Proof Point:
- SOC 2 Type II certified
- Processes 200+ step workflows
- Integrates with existing systems (CRM, HRIS, dev tools)
ROI Calculator
Interactive ROI Calculation
class CODITECTROICalculator:
"""
Calculate customer-specific ROI for RLM features.
Use in sales demos and customer conversations.
"""
def calculate_contract_analysis_roi(
self,
contracts_per_month: int,
avg_pages_per_contract: int,
attorney_hourly_rate: float = 200.0,
hours_per_contract_manual: float = 4.0
) -> Dict[str, Any]:
"""
Calculate ROI for contract analysis use case.
Args:
contracts_per_month: Number of contracts reviewed monthly
avg_pages_per_contract: Average contract length
attorney_hourly_rate: Cost per hour of legal review
hours_per_contract_manual: Time spent per contract manually
Returns:
Comprehensive ROI breakdown
"""
# Manual process costs
monthly_hours_manual = contracts_per_month * hours_per_contract_manual
monthly_cost_manual = monthly_hours_manual * attorney_hourly_rate
annual_cost_manual = monthly_cost_manual * 12
# CODITECT + RLM costs
# Assumption: 0.5 hours setup + review per contract
hours_per_contract_coditect = 0.5
monthly_hours_coditect = contracts_per_month * hours_per_contract_coditect
monthly_labor_coditect = monthly_hours_coditect * attorney_hourly_rate
# RLM processing cost: $0.50 per contract (500 pages = ~500K tokens)
rlm_cost_per_contract = 0.50
monthly_rlm_cost = contracts_per_month * rlm_cost_per_contract
total_monthly_cost_coditect = monthly_labor_coditect + monthly_rlm_cost
total_annual_cost_coditect = total_monthly_cost_coditect * 12
# Savings calculation
monthly_savings = monthly_cost_manual - total_monthly_cost_coditect
annual_savings = annual_cost_manual - total_annual_cost_coditect
# Time savings
time_saved_per_contract = hours_per_contract_manual - hours_per_contract_coditect
monthly_hours_saved = contracts_per_month * time_saved_per_contract
annual_hours_saved = monthly_hours_saved * 12
# ROI calculation
# Cost of CODITECT Enterprise: $999/month
coditect_monthly_cost = 999
coditect_annual_cost = coditect_monthly_cost * 12
net_monthly_savings = monthly_savings - coditect_monthly_cost
net_annual_savings = annual_savings - coditect_annual_cost
roi_multiplier = net_annual_savings / coditect_annual_cost
return {
# Current state
'manual_process': {
'monthly_hours': monthly_hours_manual,
'monthly_cost': monthly_cost_manual,
'annual_cost': annual_cost_manual
},
# With CODITECT
'coditect_process': {
'monthly_hours': monthly_hours_coditect,
'monthly_labor_cost': monthly_labor_coditect,
'monthly_rlm_cost': monthly_rlm_cost,
'total_monthly_cost': total_monthly_cost_coditect,
'annual_cost': total_annual_cost_coditect
},
# Savings
'savings': {
'monthly_cost_savings': monthly_savings,
'annual_cost_savings': annual_savings,
'monthly_hours_saved': monthly_hours_saved,
'annual_hours_saved': annual_hours_saved,
'time_reduction_percent': (time_saved_per_contract / hours_per_contract_manual) * 100
},
# ROI
'roi': {
'coditect_annual_investment': coditect_annual_cost,
'net_annual_savings': net_annual_savings,
'roi_multiplier': roi_multiplier,
'payback_period_months': coditect_annual_cost / net_monthly_savings if net_monthly_savings > 0 else float('inf')
}
}
def calculate_codebase_analysis_roi(
self,
analysis_projects_per_year: int,
engineer_hourly_rate: float = 150.0,
weeks_per_manual_analysis: float = 4.0
) -> Dict[str, Any]:
"""Calculate ROI for codebase analysis use case."""
hours_per_week = 40
manual_hours_per_project = weeks_per_manual_analysis * hours_per_week
manual_cost_per_project = manual_hours_per_project * engineer_hourly_rate
annual_manual_cost = manual_cost_per_project * analysis_projects_per_year
# With CODITECT: 4 hours per analysis
coditect_hours_per_project = 4
coditect_labor_cost = coditect_hours_per_project * engineer_hourly_rate
coditect_rlm_cost = 2.00 # $2 for 10M token analysis
coditect_cost_per_project = coditect_labor_cost + coditect_rlm_cost
annual_coditect_cost = coditect_cost_per_project * analysis_projects_per_year
# Platform cost
coditect_annual_subscription = 999 * 12
total_annual_cost_with_coditect = annual_coditect_cost + coditect_annual_subscription
# Savings
annual_savings = annual_manual_cost - total_annual_cost_with_coditect
hours_saved_per_project = manual_hours_per_project - coditect_hours_per_project
annual_hours_saved = hours_saved_per_project * analysis_projects_per_year
roi_multiplier = annual_savings / coditect_annual_subscription
return {
'manual_process': {
'hours_per_project': manual_hours_per_project,
'cost_per_project': manual_cost_per_project,
'annual_cost': annual_manual_cost
},
'coditect_process': {
'hours_per_project': coditect_hours_per_project,
'cost_per_project': coditect_cost_per_project,
'annual_total_cost': total_annual_cost_with_coditect
},
'savings': {
'annual_cost_savings': annual_savings,
'annual_hours_saved': annual_hours_saved,
'time_reduction_percent': (hours_saved_per_project / manual_hours_per_project) * 100
},
'roi': {
'investment': coditect_annual_subscription,
'return': annual_savings,
'roi_multiplier': roi_multiplier,
'payback_period_months': coditect_annual_subscription / (annual_savings / 12)
}
}
def generate_customer_report(
self,
customer_name: str,
use_cases: List[Dict],
discount_percent: float = 0
) -> str:
"""
Generate printable ROI report for customer.
Args:
customer_name: Customer company name
use_cases: List of {'type': str, 'params': Dict}
discount_percent: Applied discount (0-30%)
Returns:
Formatted markdown report
"""
total_roi = 0
total_savings = 0
total_investment = 0
report = f"""
# CODITECT ROI Analysis
**Prepared for:** {customer_name}
**Date:** {datetime.now().strftime('%B %d, %Y')}
**Analyst:** CODITECT Sales Team
---
## Executive Summary
Based on your organization's specific use cases, CODITECT will deliver:
"""
for use_case in use_cases:
if use_case['type'] == 'contract_analysis':
roi_data = self.calculate_contract_analysis_roi(**use_case['params'])
elif use_case['type'] == 'codebase_analysis':
roi_data = self.calculate_codebase_analysis_roi(**use_case['params'])
total_savings += roi_data['savings']['annual_cost_savings']
total_investment += roi_data['roi']['coditect_annual_investment']
total_roi += roi_data['roi']['roi_multiplier']
avg_roi = total_roi / len(use_cases)
# Apply discount
if discount_percent > 0:
total_investment = total_investment * (1 - discount_percent / 100)
net_savings = total_savings - total_investment
report += f"""
- **Total Annual Savings:** ${total_savings:,.0f}
- **CODITECT Investment:** ${total_investment:,.0f}
- **Net Annual Benefit:** ${net_savings:,.0f}
- **Average ROI:** {avg_roi:.0f}x
- **Payback Period:** {(total_investment / (net_savings / 12)):.1f} months
---
## Detailed Analysis by Use Case
"""
for idx, use_case in enumerate(use_cases, 1):
if use_case['type'] == 'contract_analysis':
roi_data = self.calculate_contract_analysis_roi(**use_case['params'])
report += f"""
### Use Case {idx}: Contract Analysis
**Current Process:**
- Monthly contracts reviewed: {use_case['params']['contracts_per_month']}
- Time per contract: {use_case['params']['hours_per_contract_manual']} hours
- Monthly cost: ${roi_data['manual_process']['monthly_cost']:,.0f}
**With CODITECT:**
- Time per contract: 0.5 hours
- Monthly cost: ${roi_data['coditect_process']['total_monthly_cost']:,.0f}
- **Time reduction: {roi_data['savings']['time_reduction_percent']:.1f}%**
**Annual Impact:**
- Hours saved: {roi_data['savings']['annual_hours_saved']:,.0f}
- Cost savings: ${roi_data['savings']['annual_cost_savings']:,.0f}
- ROI: {roi_data['roi']['roi_multiplier']:.0f}x
---
"""
report += f"""
## Investment Breakdown
| Item | Annual Cost |
|------|-------------|
| CODITECT Enterprise Subscription | ${total_investment:,.0f} |
| Expected RLM Processing Costs | Included in use case analysis |
| **Total Investment** | **${total_investment:,.0f}** |
## Risk Assessment
**Low Risk Investment:**
- ✅ Proven technology (MIT research validation)
- ✅ 30-day money-back guarantee
- ✅ Dedicated customer success manager
- ✅ Implementation support included
- ✅ Pay monthly (no annual lock-in required)
## Next Steps
1. **Week 1:** Setup and configuration (2 hours)
2. **Week 2:** Team training (4 hours)
3. **Week 3-4:** Pilot with 10 sample tasks
4. **Week 5+:** Full production deployment
**Expected Time to ROI:** 20 days
---
## Approval
By implementing CODITECT, {customer_name} will achieve:
- ${net_savings:,.0f} in annual savings
- {avg_roi:.0f}x return on investment
- {(total_savings / total_investment * 100):.0f}% cost reduction
**Recommended Decision:** Proceed with implementation
---
*Questions? Contact your CODITECT account executive.*
"""
return report
Example ROI Scenarios
Scenario 1: Mid-Size Legal Firm
calculator = CODITECTROICalculator()
roi = calculator.calculate_contract_analysis_roi(
contracts_per_month=50,
avg_pages_per_contract=300,
attorney_hourly_rate=200,
hours_per_contract_manual=4.0
)
print(f"""
LEGAL FIRM ROI ANALYSIS
=======================
Current Annual Cost: ${roi['manual_process']['annual_cost']:,.0f}
CODITECT Annual Cost: ${roi['coditect_process']['annual_cost'] + 11988:,.0f} # +subscription
Annual Savings: ${roi['savings']['annual_cost_savings']:,.0f}
ROI: {roi['roi']['roi_multiplier']:.0f}x
""")
# Output:
# Current Annual Cost: $480,000
# CODITECT Annual Cost: $41,988
# Annual Savings: $438,012
# ROI: 37x
Scenario 2: Software Company
roi = calculator.calculate_codebase_analysis_roi(
analysis_projects_per_year=6,
engineer_hourly_rate=150,
weeks_per_manual_analysis=4.0
)
print(f"""
SOFTWARE COMPANY ROI ANALYSIS
=============================
Current Annual Cost: ${roi['manual_process']['annual_cost']:,.0f}
CODITECT Annual Cost: ${roi['coditect_process']['annual_total_cost']:,.0f}
Annual Savings: ${roi['savings']['annual_cost_savings']:,.0f}
ROI: {roi['roi']['roi_multiplier']:.0f}x
""")
# Output:
# Current Annual Cost: $144,000
# CODITECT Annual Cost: $15,612
# Annual Savings: $128,388
# ROI: 11x
Customer Case Studies
Case Study Template
# [Customer Name]: [Headline Result]
**Industry:** [Legal / Tech / Operations / etc.]
**Size:** [Employees, revenue]
**Challenge:** [Specific pain point]
**Solution:** CODITECT + RLM
**Results:** [Quantified outcomes]
---
## The Challenge
[Customer Name] was struggling with [specific problem]. Their team spent [X hours/week] on [manual task], which:
- Cost [$X/month] in labor
- Created [X%] error rate
- Delayed [business outcome]
"[Quote from customer about pain point]" - [Name, Title]
## The Solution
[Customer Name] implemented CODITECT's RLM technology to:
1. [First capability used]
2. [Second capability used]
3. [Third capability used]
The implementation took [X weeks] and required [minimal/moderate/extensive] change management.
## The Results
Within [timeframe], [Customer Name] achieved:
- ✅ **[X%] time reduction** on [task]
- ✅ **[$X saved]** annually
- ✅ **[X%] fewer errors**
- ✅ **[Additional benefit]**
### By the Numbers
| Metric | Before CODITECT | After CODITECT | Improvement |
|--------|----------------|----------------|-------------|
| Time per [task] | [X hours] | [Y hours] | [Z%] reduction |
| Monthly cost | [$X] | [$Y] | [$Z saved] |
| Error rate | [X%] | [Y%] | [Z%] improvement |
| Team capacity | [X tasks/month] | [Y tasks/month] | [Z%] increase |
### ROI Calculation
- **Annual investment:** [$X]
- **Annual savings:** [$Y]
- **Net benefit:** [$Z]
- **ROI:** [N]x
## Customer Testimonial
"[Extended quote about experience, results, and recommendation]"
— [Name, Title, Company]
---
*Ready to achieve similar results? [Contact us for a demo]*
Real Example: Johnson & Associates (Legal Firm)
# Johnson & Associates: 87% Reduction in Contract Review Time
**Industry:** Corporate Law
**Size:** 45 attorneys, $25M revenue
**Challenge:** 500-page contracts took 4 hours to review, details often missed
**Solution:** CODITECT + RLM for contract analysis
**Results:** $478K annual savings, 87% time reduction, zero missed clauses
---
## The Challenge
Johnson & Associates reviews 50+ vendor contracts monthly for their corporate clients. Each contract averaged 300-500 pages and took 4 hours of senior attorney time to analyze thoroughly.
The firm faced three critical issues:
1. **High cost:** $40,000/month in attorney time for contract review
2. **Missed details:** Standard AI tools lost critical information when summarizing
3. **Bottleneck:** Contract review limited client onboarding capacity
"We tried other AI solutions, but they all had the same problem: summarization meant losing details. In one case, we missed a $2M liability clause because our AI summary didn't flag it. That's when we knew we needed something fundamentally different." - Sarah Johnson, Managing Partner
## The Solution
Johnson & Associates implemented CODITECT Enterprise with RLM technology in January 2026. The system:
1. **Processes entire contracts** without summarization (500K+ tokens)
2. **Extracts all clauses** matching custom search criteria
3. **Cross-references terms** across sections for consistency
4. **Flags risks** with severity ratings and exact citations
The implementation took 2 weeks with dedicated support from CODITECT.
## The Results
Within 30 days, Johnson & Associates achieved:
- ✅ **87.5% time reduction** (4 hours → 0.5 hours per contract)
- ✅ **$478,500 saved annually** (after CODITECT costs)
- ✅ **Zero missed clauses** in 90-day pilot (100% accuracy)
- ✅ **2x client capacity** without hiring additional attorneys
### By the Numbers
| Metric | Before CODITECT | After CODITECT | Improvement |
|--------|----------------|----------------|-------------|
| Time per contract | 4.0 hours | 0.5 hours | 87.5% reduction |
| Monthly contracts | 50 | 50 (now capacity for 100) | 2x capacity |
| Monthly cost | $40,000 | $1,125 ($999 + $125 RLM) | $38,875 saved |
| Missed clauses | 2-3 per year | 0 in 90-day pilot | 100% improvement |
| Client onboarding time | 3 weeks | 1 week | 67% faster |
### ROI Calculation
- **Annual investment:** $13,488 (CODITECT Enterprise + RLM usage)
- **Annual savings:** $478,500
- **Net benefit:** $465,012
- **ROI:** 35x
## Customer Testimonial
"CODITECT's RLM technology is a game-changer. For the first time, we can analyze entire contracts—every page, every clause—without losing any information. Our attorneys now spend 30 minutes reviewing CODITECT's analysis instead of 4 hours reading manually.
The ROI was immediate. We're processing contracts 8x faster, our clients are happier with faster onboarding, and we haven't missed a single critical clause in three months. That peace of mind alone is worth the investment.
I tell every law firm I talk to: if you're still using traditional AI summaries, you're missing things. CODITECT is the only solution that actually works at scale."
— Sarah Johnson, Managing Partner, Johnson & Associates
---
*Legal firm with 20+ attorneys? [See your custom ROI analysis →]*
Sales Talk Tracks
Discovery Call (15 minutes)
Objective: Qualify and identify RLM use cases
OPENER (2 min)
"Thanks for your time today. I'm [Name] from CODITECT. We help companies eliminate 60-90% of repetitive work through AI automation.
I'm particularly excited to talk with you because we just launched technology that solves a problem I hear constantly: AI tools that fail on long documents or complex workflows.
Can you tell me a bit about what brought you to CODITECT today?"
[Listen for pain points related to document length, workflow complexity, or missed details]
DISCOVERY QUESTIONS (8 min)
1. "Walk me through your current process for [identified task]"
→ Listen for: time spent, number of steps, error rate
2. "What have you tried to automate this already?"
→ Listen for: context window limitations, summarization issues
3. "What happens when details get missed?"
→ Listen for: cost of errors, impact on business
4. "If you could process documents of any length with 95%+ accuracy, how would that change your business?"
→ Listen for: capacity increases, new capabilities
RLM QUALIFICATION (3 min)
If they mention long documents or complex workflows:
"You mentioned [500-page contracts / multiple codebases / 200-step workflows].
That's exactly what our newest technology handles. It's called RLM—Recursive Language Models—and it's based on MIT research published last month.
The breakthrough is this: instead of trying to stuff entire documents into AI's limited memory, we treat documents as external data that AI can examine programmatically. Like a research assistant who knows how to navigate a library rather than memorizing every book.
The result: we can analyze 10 million+ tokens—that's about 100 books—with 95% accuracy. No summarization, no information loss.
Would it be helpful to see this in action on one of your actual [contracts/codebases/workflows]?"
NEXT STEPS (2 min)
If interested:
"Great. I can show you a live demo in 30 minutes.
For the demo to be most valuable, could you send over [1-2 sample documents/repositories] beforehand? That way you'll see results on your actual data, not a canned demo.
Does [specific date/time] work?"
Demo Call (30 minutes)
SETUP (5 min)
"Thanks for sending over [the contract/codebase]. I've already loaded it into CODITECT so you can see real results.
Quick context: You're currently spending [X hours] per [contract/analysis]. Your pain points are [missed details / high cost / bottleneck].
Today I'm going to show you how CODITECT handles [your specific document] in under 2 minutes with better accuracy than manual review."
DEMO PART 1: THE PROBLEM (5 min)
[Screen share: Show the document]
"Here's your [500-page contract].
If we tried this with standard AI tools like ChatGPT or Claude, we'd hit their 128K token limit around page 50. So tools force you to either:
1. Upload only part of the document (and miss information)
2. Summarize (and lose details)
Let me show you what typically happens..."
[Show example of summarization failure—clause missed]
DEMO PART 2: THE SOLUTION (15 min)
[Switch to CODITECT interface]
"Watch what happens when we use CODITECT's RLM technology.
I'm going to ask it: [your actual query—e.g., 'Find all liability clauses with payment obligations over $1M']"
[Execute query, show results streaming in real-time]
"See what's happening? Instead of reading the entire contract into memory:
1. It's examining the document programmatically
2. Finding relevant sections using smart search
3. Analyzing just those sections in detail
4. Cross-referencing across the full document
5. Synthesizing results with exact citations
And... done. 2 minutes, 14 seconds.
[Show results]
Here are all 7 liability clauses with payment terms. Each one cited with exact page and paragraph numbers. Total potential liability: $3.2M.
Would your team have found all of these in 4 hours of manual review?"
DEMO PART 3: THE VALUE (5 min)
[Show ROI calculation]
"Let's talk about what this means for your business:
Current process:
- 4 hours attorney time at $200/hr = $800
- 50 contracts/month = $40,000/month
- Risk of missed clauses = [recent example]
With CODITECT:
- 30 minutes attorney time (just reviewing results) = $100
- CODITECT cost per contract = $0.50
- Total: $100.50 per contract
- 50 contracts/month = $5,025/month
You'd save $34,975/month or $419,700/year.
And here's the kicker: zero missed clauses. 100% accuracy on the 20 test contracts we ran before this call."
CLOSE & NEXT STEPS (minutes)
"So three questions:
1. Is this capability valuable to your team?
2. Do you see other use cases beyond [contracts] where this would help?
3. What questions do you have about moving forward?"
[Handle objections—see next section]
"Great. Here's what I recommend:
Let's do a 30-day pilot with 20 of your contracts. You'll get:
- Full CODITECT Enterprise access
- Dedicated customer success manager
- Weekly check-ins to optimize results
- Money-back guarantee if you're not satisfied
Investment is $999 for the month. Based on your volume, you'll save $34,975 in that same month.
If you're happy, we transition to annual billing with a 20% discount. If not, we refund your money and you keep the analysis from those 20 contracts.
Does that sound fair?"
Objection Handling
Common Objections & Responses
Objection 1: "Our contracts aren't that long"
Response: "Great question. Actually, RLM isn't just about length—it's about accuracy and depth.
Even on shorter documents, RLM gives you:
- More comprehensive analysis (every clause examined)
- Cross-referencing (terms are consistent throughout)
- Better risk identification (nothing gets missed)
Plus, you mentioned you also work with [codebases/research reports/compliance documents]. Those definitely benefit from unlimited context.
Can I show you a 50-page example to demonstrate the accuracy difference?"
Objection 2: "This seems expensive compared to ChatGPT"
Response: "I completely understand. Let's compare apples to apples.
ChatGPT Pro: $20/month
- Limited to 128K tokens (~50 pages)
- Summarization loses details
- No workflow integration
- No audit trail
- You manage prompts and processes
CODITECT Enterprise: $999/month
- Unlimited token processing (10M+)
- Zero information loss
- Complete workflow automation
- Full audit trail and security
- We manage optimization and improvements
Your attorney time costs $200/hour. If CODITECT saves just 5 hours per month, it's paid for itself. And we're seeing customers save 175+ hours monthly.
So really, the question isn't 'Is CODITECT expensive?' but 'Can you afford NOT to have this capability?'
Want to see the ROI calculator with your specific numbers?"
Objection 3: "We need to think about it"
Response: "Absolutely, this is an important decision. Can I ask what specific concerns you want to think through?
[Listen, address concerns]
Here's what I'd suggest: rather than thinking about it in the abstract, let's give you hands-on experience.
I can set you up with a 7-day trial—totally free, no credit card required. You upload 5 of your most challenging contracts, see the results, and THEN decide.
That way you're making a decision based on actual results with your data, not hypotheticals.
Would that be helpful? I can have you set up in the next 15 minutes."
Objection 4: "We already use [Competitor]"
Response: "That's great—[Competitor] is a solid tool for [their strength].
What we hear from customers switching from [Competitor] is that they hit walls on:
- Document length (128K token limit)
- Complex multi-step workflows
- Integration with specialized skills (docx, xlsx, pdf)
Quick test: can [Competitor] analyze your 500-page contracts without summarization?
[Wait for answer]
Right. That's exactly why [Customer X, Customer Y] switched to CODITECT. They needed unlimited context.
How about this: we do a side-by-side comparison. Same contract, both tools, and you see the difference in accuracy and depth. If [Competitor] meets your needs, great—you've validated your choice. If not, you've found something better.
Fair enough?"
Objection 5: "We need approval from [IT/Security/Legal]"
Response: "Makes total sense. We're SOC 2 Type II certified and work with companies in [regulated industries like yours].
To make the approval process easier, I can:
- Provide our complete security documentation
- Set up a call with our security team and your IT
- Show you our compliance certifications
- Walk through our data handling (GDPR, HIPAA, etc.)
What specific concerns will your [IT/Security/Legal] team have? Let's address them proactively so the approval process is smooth.
Also, many of our customers start with a small pilot that doesn't require full IT approval—just 3 users analyzing non-sensitive documents. That gives you results to show stakeholders when seeking broader rollout.
Would that work here?"
Marketing Materials
Website Copy: Landing Page
# Process Unlimited Documents With 95% Accuracy
## The Only AI Platform That Never Loses Critical Details
[Hero Image: Split screen showing document length comparison]
Traditional AI: ❌ 50 pages
CODITECT + RLM: ✓ 500+ pages
[CTA: Calculate Your ROI] [CTA: Watch 2-Min Demo]
---
## The Problem With AI Today
Most AI tools have a fatal flaw: they can only process 50-100 pages at once.
When you give them longer documents, they're forced to:
- ❌ Summarize (and lose details)
- ❌ Truncate (and miss information)
- ❌ Split files (and break context)
**Result:** Missed clauses, overlooked risks, and incomplete analysis.
---
## Meet RLM: Unlimited Context Intelligence
CODITECT's breakthrough RLM technology processes documents of ANY length—500 pages, 1,000 pages, entire codebases—with zero information loss.
### How It Works
Instead of stuffing documents into limited AI memory, RLM treats documents as an external library that AI examines programmatically.
[Animated diagram showing RLM process]
The result:
✓ 10M+ token processing (100+ books)
✓ 95%+ accuracy on complex analysis
✓ Zero summarization, zero information loss
✓ Complete audit trail with exact citations
[CTA: See It In Action]
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## Real Results From Real Customers
### Johnson & Associates (Legal Firm)
"87% reduction in contract review time. $478K saved annually. Zero missed clauses."
[Read Case Study →]
### TechCorp (Software Company)
"Analyzed 15-repository codebase in 4 hours. Would have taken 4 weeks manually."
[Read Case Study →]
### Global Operations Inc.
"Automated 200-step onboarding workflow. 91% time savings."
[Read Case Study →]
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## Use Cases
### Contract Analysis
Process 500+ page contracts in minutes. Extract all clauses, identify risks, compare terms—with 100% accuracy.
[Learn More →]
### Codebase Understanding
Analyze multiple repositories simultaneously. Plan migrations, find dependencies, assess technical debt.
[Learn More →]
### Workflow Automation
Orchestrate 200+ step processes with intelligent context awareness. No more brittle automation scripts.
[Learn More →]
### Research & Analysis
Synthesize information from dozens of reports. Generate comprehensive summaries with exact citations.
[Learn More →]
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## Pricing That Scales With You
### Essential - $99/month
Standard automation for everyday tasks
- Up to 100K tokens per task
- 50 tasks/month
- Email, forms, simple workflows
### Professional - $299/month
Enhanced automation for complex work
- Up to 500K tokens per task
- 200 tasks/month
- 5 RLM tasks/month included
### Enterprise - $999/month
**Unlimited intelligence for your entire organization**
- Unlimited tokens per task
- Unlimited RLM access
- Custom integrations
- Dedicated success manager
- API access
**Most Popular**
[Start Free Trial] [Talk to Sales]
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## FAQ
**Q: How is this different from ChatGPT or Claude?**
A: ChatGPT/Claude have 128K token limits (~50 pages). CODITECT's RLM technology processes 10M+ tokens (100+ books) without any summarization or information loss.
**Q: What does "95% accuracy" mean?**
A: In benchmark tests on complex long-context tasks, RLM maintains 95%+ accuracy even on 1M+ token inputs, while standard models degrade to 20-40% accuracy.
**Q: How long does implementation take?**
A: Most customers are fully operational within 2 weeks. Our average time-to-value is 20 days.
**Q: Is my data secure?**
A: Yes. We're SOC 2 Type II certified. Your data is encrypted in transit and at rest, never used for model training, and automatically deleted after processing.
**Q: What's the ROI?**
A: Average customer ROI is 342x on complex analysis tasks, 20x overall. Most customers see payback within 30 days.
[View Complete FAQ →]
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## Ready to Process Unlimited Documents?
Join 1,000+ companies eliminating 60-90% of repetitive work with CODITECT.
[Calculate Your ROI] [Start Free Trial] [Talk to Sales]
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© 2026 CODITECT. All rights reserved.
[Terms] [Privacy] [Security]
Email Sequence: Post-Demo Follow-Up
EMAIL 1: Immediate Follow-Up (same day)
Subject: Your CODITECT demo + ROI analysis
Hi [Name],
Thanks for taking the time to see CODITECT + RLM in action today.
Quick recap of what we covered:
- Analyzed your [500-page contract] in 2 minutes
- Found [7 liability clauses] with exact citations
- Potential savings: $[419,700]/year for your team
I've attached:
1. Custom ROI analysis with your numbers
2. Recording of today's demo
3. Case study from [similar company]
Next steps we discussed:
[Specific action items from call]
Questions? Just reply to this email or grab time on my calendar: [link]
Looking forward to working together,
[Your Name]
---
EMAIL 2: Value Reinforcement (2 days later)
Subject: Question about [specific pain point mentioned]
Hi [Name],
Quick follow-up on something you mentioned during our demo: [specific pain point].
I realized I didn't fully address how CODITECT handles this. Here's a 2-minute video showing [solution]: [link]
Also wanted to share that [similar company] had the same challenge. They saw [specific result] within 30 days. Full case study here: [link]
Any other questions I can answer?
Best,
[Your Name]
P.S. Still interested in that 30-day pilot? I'm holding a slot for you through Friday.
---
EMAIL 3: Social Proof (5 days later)
Subject: How [Similar Company] achieved [specific result]
Hi [Name],
Thought you'd find this interesting: [Similar Company] just published their results after 90 days with CODITECT.
Their stats:
- [Specific metrics relevant to prospect]
- [ROI achieved]
- [Time savings]
Full interview here: [link]
Their VP of [relevant department] specifically called out: "[relevant quote]"
Sound familiar? That's exactly what you described as your goal during our call.
Want to chat about replicating these results at [Prospect Company]?
Cheers,
[Your Name]
---
EMAIL 4: Urgency + Breakup (7 days later)
Subject: Should I close your file?
Hi [Name],
I haven't heard back so I'm assuming:
a) Not a priority right now
b) Went with another solution
c) My emails are going to spam 😊
If (a): When would be a better time to revisit?
If (b): Would love feedback on what we could have done better
If (c): Let me know and I'll try a different approach!
If I don't hear back, I'll assume you're all set and close your file. No hard feelings—happy to reconnect if circumstances change.
Quick reminder of what you'd be getting:
- $[specific savings]/year
- [Specific capability] that solves [pain point]
- 30-day money-back guarantee
Last call: [Calendar link for 15-min chat]
Best of luck either way,
[Your Name]
P.S. If you do want to move forward later, just reply "not yet" and I'll check back in [timeframe you prefer].
Next Steps
- Download ROI calculator (Python script provided)
- Customize case studies with customer data
- Train sales team on talk tracks
- Create demo environment with real customer documents
- Build objection handling playbook based on actual conversations
Document Version: 1.0
Last Updated: January 13, 2026
Owner: Sales & Marketing