Enterprise AI spend reduction

Useful intelligence. Fewer tokens. Lower watts.

Offlyn helps teams reduce annual AI spend by auditing token-heavy workflows and implementing offline-first, hybrid AI routing.

Built from Clipper, Apply, TerraGuide, and the open-source Token Savings Audit.

Product proof points

Clipper, Apply, and TerraGuide prove the local-first capabilities behind Offlyn’s enterprise audit stack.

Each product demonstrates a reusable enterprise capability: local inference, private memory, compact context, offline workflows, or cloud fallback only when needed.

Clipper

Clipper

NOW LIVE

Local meeting intelligence for Mac.

On-device transcription, private meeting memory, hybrid search, and no meeting bots.

Enterprise proof: meeting workflow token savings, transcript compression, local transcription, and private retrieval.

  • Local transcription and meeting memory
  • Transcript compression and reuse
  • Private search across meetings and documents
  • Benchmark foundation for meeting-intelligence audits

We find where your AI budget is leaking tokens.

Offlyn works across Finance, Product, and Engineering to identify AI workflows driving annual spend, then redesigns them with local-first processing, compact cloud fallback, and measurement instrumentation.

1

Map spend

Top AI vendor costs and COGS drivers.

2

Audit tokens

Prompts, traces, transcripts, RAG chunks.

3

Route intelligence

Local, cached, or cloud reasoning.

4

Measure quality

Quality gates and fallback behavior.

5

Report outcomes

Annual spend, tokens, privacy, carbon.

Choose your path to fewer tokens and lower watts.

Tier 1

Self-Serve AI Resource Audit

Run the open-source calculator with your own assumptions.

Modeled annual AI spend reduced

Tier 2

Forward-Deployed GreenOps Audit

Offlyn engineers instrument real workflows and measure annualized savings.

Measured annualized AI spend reduced

Tier 3

Offline AI Roadmap + Assurance Packet

Design hybrid AI routing across meetings, documents, field workflows, and edge devices.

Projected portfolio-level AI spend reduced

Start with the open-source audit.

Estimate token savings, cost reduction, and operational carbon intensity with configurable assumptions, JSON/CSV exports, and claims-safe disclosure language.

View GitHub Repo

Future research: useful intelligence per token, per dollar, per watt.

Products and audits create a feedback loop for local models, hybrid routers, edge inference, and SCI-AI-aligned measurement.

Hybrid routing Local model optimization Context compression Quality gates Offline memory Edge resilience SCI-AI-aligned reporting

Enterprise AI efficiency, built from product proof points.

Offlyn packages local-first techniques into Token Savings Audits, hybrid routing designs, context optimizers, and offline AI roadmaps for enterprise teams.

Token Savings Audit

Estimate annual AI spend reduced across cloud-first, offline-first, and hybrid workflows.

Context Optimizer

Compile transcripts, documents, logs, and RAG chunks into compact evidence packs.

Hybrid Router

Route tasks across local, small, cloud, and human-review layers by quality, risk, cost, and privacy.

MLX / Local AI

Optimize Apple Silicon and local inference for transcription, embeddings, and private search.

Audit outputs may be modeled or measured depending on engagement tier. Offlyn does not claim guaranteed savings, certified token reductions, verified emissions reductions, carbon neutrality, or water-free AI. SCI-AI-aligned metrics are ISO/IEC 21031:2024-informed operational proxy estimates unless and until a public certificate is issued for the relevant disclosure.

TerraGuide Privacy Policy

TerraGuide operates completely offline and does not collect personal data. Any information you enter remains on your device to support app functionality.

We do not transmit or store your data on our servers. Diagnostic logs stay local and are deleted when you remove the app.

We never share your information with third parties. You may request deletion of any support communications by contacting us.

Contact: hi@offlyn.ai