Retenna watches what is happening across the business and outside it, catches important risks and opportunities early, explains what they affect, helps the right people and AI act, and checks the result so the next decision is better. It is one company-wide system for noticing, deciding, coordinating, acting and learning.
Illustrative example · Northstar Software
Leaders still have to notice important changes, work out what they affect, make the decision, coordinate the work and check whether the business improved. More tools and more AI create more activity without closing that loop.
Retenna keeps the whole loop connected.
A late task, quiet customer, support complaint, competitor move or blocked dependency may look small alone. Their combined effect becomes clear only after the cost has grown.
A goal still looks active while the work beneath it slips. Teams follow different decisions, deadlines lose owners and customer promises separate from delivery.
One project delay can affect revenue, customers, another team and the board plan at once. Existing systems show the local issue, not the company-wide impact.
Different workers investigate separate versions of the same problem, miss dependencies and make decisions without seeing what is already under way.
An AI may complete its task without knowing the current priority, what it may change, who else is involved, when approval is required or whether its work helped.
The email is sent, the ticket closes and the AI finishes. The company still may not know whether the customer recovered, the project returned to plan or the same mistake should be prevented next time.
Retenna keeps the company’s goals, decisions, commitments, work and results connected, then uses that understanding to guide what happens next.
Retenna follows approved internal work and outside developments, looking for material changes before someone asks the right question.
It connects each change to the customers, goals, decisions, promises, projects, deadlines, risks and opportunities it affects.
Retenna brings forward the evidence, previous decisions, uncertainty, options and trade-offs needed to choose the next move.
It gives each worker a clear part of the same result, keeps active work visible and prevents duplication or conflict.
Retenna can recommend, prepare work for approval or carry out approved low-risk action where the connected system allows it.
It follows the result. Successful approaches spread, corrections change future work and failed approaches become harder to repeat.
Keep Northstar and deliver a credible fix before renewal.
Usage down · support worsening · promised fix late.
Renewal · delivery promise · Q3 revenue plan.
Who does what
Find material internal and external changes before they become obvious surprises.
Explain what changed, what it affects, what remains uncertain and which decision is needed.
Deliver the priorities, unresolved work and risks each person needs to act on.
Give people and AI clear responsibilities, shared goals, hand-offs and deadlines.
Prepare or carry out approved work with the right limits, review and record.
Keep decisions, corrections, actions and results so future work starts better informed.
Retenna has moved from thesis to private beta, with early company demand and operator backing.
Built by a solo technical founder from company sources and risk detection through coordinated work, approvals, outside research and reviewable actions.
Companies requested private-beta access in the first month before paid advertising, an outbound sales team or a public launch.
The first outside capital came from an experienced operator adviser who also supports commercial strategy and execution.
As AI gains access to more company systems, businesses need one layer that keeps its work aligned with company priorities and measures whether it improved the business.
Enterprise spending grew 3.2× in one year.
More than half of enterprise generative-AI spending already sits at the application layer.
Gartner cites rising cost, unclear value and weak controls.
OpenAI, Microsoft and Glean are proving the access layer. Retenna connects that access to company priorities, people, decisions and results across the whole business.
SOURCES: MENLO VENTURES · 2025 STATE OF GENERATIVE AI IN THE ENTERPRISE · GARTNER · AGENTIC AI PROJECT FORECAST, 25 JUNE 2025 · OPENAI COMPANY KNOWLEDGE · MICROSOFT WORK IQ · GLEAN PRODUCT MATERIALS
Initial focus: 20–200-person B2B companies where customer promises, projects and decisions already cross several teams, systems and AI tools.
INITIAL CUSTOMER
Growing companies with enough complexity for important work to fall between teams, but without the appetite for a heavyweight enterprise rollout.
FIRST PROBLEM
Start where late awareness, poor coordination or weak follow-through already costs the company money or time.
Use the approved apps, information and actions required for that problem — nothing broader by default.
Define the business result Retenna should improve, not merely the task it should complete.
Begin with visibility or prepared work, keep sensitive decisions with people and measure the result.
Move to an annual company subscription and add more teams, problems and approved actions as value is proven.
Retenna sells to the company rather than charging for each employee, connector or AI agent.
COMPANY
Quoted by company size and agreed rollout requirements — not by connector, tool, team, seat, problem or AI agent.
ENTERPRISE
For company-wide use with additional security, retention, legal, procurement or implementation requirements.
DESIGN PARTNERS
Selected companies work closely with Retenna on real problems before choosing paid access.
Illustrative scale only; not public pricing.
SOURCE FOR MARKET CONTEXT: MENLO VENTURES · 2025 STATE OF GENERATIVE AI IN THE ENTERPRISE
Retenna wins by solving the whole-company job incumbents only cover in pieces, entering through a faster mid-market route and learning from real company decisions and results.
Help a person or agent search company information, answer questions and use tools.
Watches across the company, coordinates work between people and AI and checks whether the business result improved.
Make company information easier to find, understand and use.
Connects what was found to decisions, responsibilities, action and the result that followed.
Build, run and monitor AI agents and their tasks.
Organises the wider company work around each agent and measures success at the business level.
Solves one problem deeply inside sales, support, projects, compliance or another function.
Uses one company-wide system across customer, project, revenue, risk, market and AI work.
ADVANTAGES FROM THE PRODUCT DESIGN
Retenna combines detection, impact analysis, decision support, coordinated work, controlled action and result measurement. Incumbents usually cover only parts of that loop.
Retenna can work with ChatGPT, Claude, custom agents and future models, keeping the company’s operating intelligence independent of one vendor.
The same system can start with customer risk or project drift, then expand into sales, compliance, outside change and people-and-AI work.
Retenna starts with one costly problem and approved workspace connections, avoiding the heavyweight rollout that excludes many growing companies.
ADVANTAGES THAT STRENGTHEN WITH USE
Retenna learns which decisions were made, why they were made, what followed and what actually worked — data a newly connected competitor does not have.
Owners, permissions, approvals, hand-offs and the proven strengths of each AI improve how future work is assigned and checked.
Successful responses become repeatable. Failed approaches, exceptions and corrections change future work across the company.
Each additional team and problem increases Retenna’s usefulness, strengthens the shared operating picture and raises the cost of replacing it.
TRENT HOWES · SOLO FOUNDER
Leads product, engineering, strategy, growth and partnerships.
A Discord + Patreon + Ko-fi-style platform combining community, memberships and creator payments with AI operations for content creators.
Building community and collaboration products showed how quickly decisions, ownership and important work break apart as people, systems and AI multiply.
Finance, operations and governance: more than 30 years of senior executive and managing-director experience at Bidvest Bank and Capital Group.
Commercial and enterprise execution: founder of Capital Group, a national distributor serving retailers including Makro and Walmart; adviser and first US$5,000 investor.
The capital funds product reliability, customer rollout, sales and security to turn early demand into repeatable revenue and expansion.
18–24 MONTH OPERATING PLAN
Identify the strongest starting problems, prove measurable results and build the first repeatable customer stories.
Prove repeatable founder-led sales, annual company contracts and continued customer use.
Reach strong next-round metrics with double-digit monthly growth, customer expansion and qualified pipeline coverage of at least three times the following quarter’s target.
Internal 18–24 month operating targets.
One company-wide intelligence layer across every person, system and AI the business uses.
