The Problem Space: Why 73% of Enterprise AI Projects Fail
Traditional AI projects don’t fail because of bad models; they fail because of poor data connectivity and unchecked cost scaling.
Project Failure Rate
Delayed or completely aborted due to poor data quality and inaccessible corporate knowledgebases.
Wasted Annually
Spent on slow, manual data labeling processes that never self-improve.
Cost Explosion
AI agents running without rigorous context and memory optimization drain budgets with zero improvement over time.
The Solution: The BetterAI Dual-Layer Engine
We solve this through two deeply synergistic infrastructure layers that sit directly inside your network.
1. DataReactor
The Enterprise RAG Layer. Retrieval-grade inference, priced for serious workloads.
DataReactor is the retrieval-augmented layer that serves as your intelligence gateway. It is purpose-built for mid-market and enterprise teams whose document corpora run into the hundreds of thousands or millions. It delivers dedicated indexes, single-tenant deployments, and signed citations out of the box.
2. BetterProxy
The Optimization Gateway. The fastest, cheapest path to a frontier model.
A unified endpoint that fronts OpenAI, Anthropic, Google, and Azure Foundry. It tracks token spend, manages rate limits, and enforces automated fallback logic with zero latency overhead.
Core Features & Performance Telemetry
Performance is the feature. We publish our latency budgets transparently. Every percentile in production charts live on your dashboard—not buried in a slide deck.
| Metric | Performance Guarantee | Operational Scope |
|---|---|---|
| p50 Retrieval Latency | 42ms | Ultra-fast data chunking |
| p95 Retrieval Latency | 120ms | Strict upper-bound security |
| p50 Cached Completion | 180ms | Near-instant response loops |
| Targeted Uptime | 99.95% | Enterprise-grade availability |
| Document Capacity | 100k–10M+ | Scaling per dedicated tenant |
Feature Deep-Dive
Horizontal Gateway & Routing (BetterProxy)
- 0ms Cache Hit Latency: Multi-tier algorithmic caching delivers instant responses for repeated or paraphrased enterprise queries.
- Quantized Recall: Implements Int8 embeddings to catch duplicate intent, resulting in a 90% smaller vector index while preserving perfect accuracy.
- Caveman Output (Terse Mode): Opt-in engine modification that actively strips conversational pleasantries before tokens are shipped, reducing output token volumes by up to 75%.
- No Idle Fleet Billing: Pay-as-you-go credit architecture across multiple providers rather than expensive flat subscriptions. Cache hits are completely free.
Advanced Retrieval & Security (DataReactor)
- IVF + Hamming Retrieval: Advanced, vector-optimized retrieval scaling across massive data sets.
- Signed Citations: Every answer is anchored to the exact source chunk it came from—clickable, audit-friendly, and impossible to silently fabricate.
- Hard Tenant Isolation: Every retrieval, cache lookup, and metric is keyed strictly by your internal user ID. No shared corpora, no data leakage paths.
- Upstream ACL Respect: If an employee cannot read a file within SharePoint or Google Drive, DataReactor will never surface it in their AI environments.
Architecture: Built Like Infrastructure, Not a Wrapper
DataReactor and BetterProxy operate as two statically linked services scaling independently.
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🗄️
Postgres:
Used for robust state management.
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⚡
Redis:
Optimized for hot paths and instant caching.
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🔍
Qdrant + IVF:
High-performance vector retrieval.
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🧠
TEI:
Dedicated Text Embeddings Inference.
The Self-Improving Flywheel
An autonomous loop from raw ingestion to model re-training.
1. Ingest
Live business data flows continuously from any connected source.
2. Arena Compete
Multiple LLMs run in parallel; the best output is selected via evaluation rules.
3. Output & Deploy
Winning results instantly enter production systems.
4. Re-Train
Validated output becomes localized training input for domain-specific SLMs.
Connectors: Bring the Data You Already Have
Four native enterprise connectors. Zero structural migrations required.
SharePoint
Native Microsoft Graph connection via OAuth.
Google Drive
Structured Drive API ingestion via OAuth.
FTP / FTPS
Polling-driven data sync protected via TLS.
SMB / CIFS
Secure access to on-premises network shares via Kerberos.
Real Companies. Real Business Outcomes.
We focus on high-level business KPIs—like Revenue, Gross Margin, and Inventory Turn—rather than just technical metrics.
Retail & Procurement (Duvo AI)
Outcome: €2.8M+ in annualized savings achieved within 3 months.
Execution: Autonomous agents integrated across ERP systems, supplier portals, and emails automated 80% of end-to-end supplier negotiations.
Insurance & Contracts
Outcome: $10M in structural savings realized.
Execution: Private, on-premises execution analyzed 128,000 internal contracts to automatically flag duplicate services and hidden auto-renewal clauses.
Telecom & Cost Efficiency
Outcome: 90% AI inference cost reduction.
Execution: Transitioned standard prompt pipelines into an optimized, multi-agent SLM architecture, increasing overall throughput from 8B to 27B tokens per day.
Payments & Dev Productivity
Outcome: 66% chatbot cost reduction.
Execution: Deployed private generative infrastructure on AWS, achieving a 46% developer code acceptance rate and generating over 4,000 lines of secure code.
Honest Qualification: Is BetterAI 360 Right For You?
Retrieval at this scale requires serious embedding, indexing, re-ranking, and dedicated SRE engineering to defend a 99.95% uptime SLO. We value clarity over generic sign-ups.
✅ Yes — This Is For You:
- • Mid-market or enterprise organizations (50 to 10,000+ employees).
- • Highly sensitive document corpora (HR logs, legal contracts, private R&D).
- • A strict compliance team that constantly asks: "Where did this answer come from?"
- • An existing corporate data footprint of 100k+ documents across SharePoint, Drive, or on-prem SMB.
- • You require single-tenant or completely air-gapped BYO-cloud deployment structures.
❌ No — Use Our Free Gateway Tier Instead:
- • You are a solo developer or working on a temporary hobby project.
- • Your application relies purely on the public web or generic, non-proprietary prompts.
- • You are searching strictly for the cheapest possible raw tokens, not grounded enterprise answers.
- • You need fewer than 10,000 retrieval calls per month.
Engagement Model: Quoted, Not Metered
We don't believe in pricing surprises. Every engagement reflects your actual corpus size, deployment shape, and targeted SLO—fully scoped before signing.
Pilot
From $4,000 / month
Focus: Prove value on a singular
data corpus.
Timeline: 60–90 days
Scope: One
source connector, up to 250k documents, shared SaaS infrastructure with a completely dedicated
index. Includes weekly health reviews.
Growth
From $12,000 / month (Annual Commitment)
Focus: Production-grade RAG across
departments.
Scope: All native connectors unlocked, multi-source
ingestion pipelines, fully dedicated SaaS tenant, and a strict 99.9% uptime SLO with integrated
service credits.
Enterprise
Custom Pricing (Multi-Year Terms)
Focus: Your cloud, your keys,
complete sovereignty.
Scope: Single-tenant or BYO-cloud deployment (AWS
/ Azure / GCP), 99.95% uptime SLO backed by a named SRE on-call, custom on-prem source bridges,
and full compliance support (SOC 2, HIPAA, GDPR).
Bring your corpus. We’ll quote the rest.
Tell us your document volume, your existing storage sources, and your required latency budget. We will return a binding, written architectural scope in 5 business days that you can take straight to your CFO.
Schedule Your Scoping CallInteractive Demo: Try the DataReactor Engine
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