Skip to content
FlagshipMEIA AI Platform

We build intelligent digital products.

Software.AI.Products.Agents.

InfoBee Digital Solutions designs and engineers software products, AI systems, and intelligent automation built for real-world businesses and emerging opportunities.

Flagship product

MEIA AI Platform

Market Event Impact Analysis

One event.Every stock it could move.

MEIA is a market-intelligence platform that reads a financial event and works outward from it — through the market, into sectors, down to the individual names with genuine exposure, each with a direction and a stated confidence.

  • Event
  • Market impact
  • Sector impact
  • Affected stocks
  • Direction
  • Confidence
  • Scenario analysis
  • Confirmation
MEIA · market-event-impact-analysis
Interface demo
Breaking event

Central bank signals an extended hold on rates

AI analysis
propagation mapping

Resolving transmission path, exposure set and directional framing

Market

Broad

Sectors

6 in path

Stocks

14 exposed

Affected stocksdirection · confidence
  • AAPLBullish82%
  • NVDABullish91%
  • XOMBearish76%

Illustrative interface state. Not market data, a recommendation, or investment advice.

Product engineering

Idea Product Scale

One sequence, run by one accountable team. Each phase produces something the next phase can actually build on.

  1. 01

    Discover

    Problem, users, constraints, success criteria.

  2. 02

    Architect

    Data model, boundaries, infrastructure shape.

  3. 03

    Design

    Interface, flows, states, design system.

  4. 04

    Build

    Full-stack engineering in reviewable increments.

  5. 05

    Validate

    Automated tests, failure paths, real usage.

  6. 06

    Launch

    Staged rollout, monitoring, rollback path.

  7. 07

    Scale

    Performance, cost, reliability, iteration.

AI agents

Software that works. AI that acts.

We build AI systems that combine language models, business rules, private data, software tools, and deterministic safeguards — so the intelligent part of the system is bounded by the parts that are predictable.

  1. 1Observe
  2. 2Reason
  3. 3Decide
  4. 4Act
  5. 5Learn from outcomes
Agent pipelinerunning
  1. Research agent

    Gathers and reconciles source material

    01
  2. Decision engine

    Applies business rules and thresholds

    02
  3. Tools / APIs

    Executes against real systems

    03
  4. Action

    Writes the outcome back

    04
  5. Verification

    Checks the result before it counts

    05

Every step is observable, every tool call is permissioned, and the verification stage decides whether a result is released or escalated.

Engineering principles

How we decide things.

Four positions we hold consistently, because they are the ones that determine whether software survives contact with production.

01

Product first

Technology exists to solve the product problem. The stack is chosen after the problem is understood, not before.

02

AI where it matters

We use AI where intelligence creates meaningful leverage — not because it is fashionable. A deterministic function that always works beats a model that usually does.

03

Production mindset

Architecture, reliability, security, observability and maintainability are decided at the start. They are not a phase that happens after the demo.

04

Built to evolve

Requirements change. Products should be designed for iteration rather than rewritten every time the business learns something.

Start a conversation

Let’s build something useful.

Have a product idea, a software challenge, or an AI opportunity? Let’s talk about what it would take to build it.