AI Bot Workloads
One endpoint.
Every bot workload.
InfraNistic routes every query to the right model automatically — regardless of domain, use case, or query type. No configuration. No training data. No routing rules written by hand.
📚 Knowledge Bots
Repetitive queries against a fixed knowledge domain — customer support, internal helpdesk, product FAQs
Knowledge bots ask the same questions repeatedly with minor variations. InfraNistic recognises this pattern automatically and accelerates repeated queries without any caching configuration.
| Pass | Avg Latency | p95 | Escalations | Errors |
|---|---|---|---|---|
| Pass 1 — cold start | 6,243ms | 23,611ms | 12 / 50 | 0 |
| Pass 2 — warm | 160ms | 181ms | 0 / 50 | 0 |
| Pass 3 — new session | 823ms | 4,196ms | 4 / 50 | 0 |
Pass 3 uses a partially overlapping query set — new values, same templates. Queries that overlap with pass 1 resolve instantly. New queries go through the full routing pipeline. No configuration required for either path.
Cost comparison — 150 queries
Est. always-large-model: ~$0.60 | InfraNistic Standard: ~$0.075 | Saving: ~87%
📡 Status Polling Bots
High-frequency polling for live state — order tracking, service health, incident management, market data
Status bots ask questions whose answers change over time. Every query must be answered fresh — stale answers are wrong answers. InfraNistic routes each query to the appropriate model tier based on the complexity of the question.
| Round | Avg Latency | p95 | Fast tier | Power tier |
|---|---|---|---|---|
| Round 1 — poll cycle 1 | 4,194ms | 8,488ms | 23 / 30 | 7 / 30 |
| Round 2 — poll cycle 2 | 4,812ms | 8,794ms | 20 / 30 | 10 / 30 |
| Round 3 — burst (2× volume) | 5,024ms | 8,882ms | 38 / 60 | 22 / 60 |
Escalation rate is stable across poll cycles (~33%) and burst load (~37%). p95 stays under 9s even at 2× query volume. Zero errors across all rounds.
Cost comparison — 120 queries
Est. always-large-model: ~$0.48 | InfraNistic Standard: ~$0.06 | Saving: ~87%
Why per-query routing varies: Status queries are inherently in the middle of the difficulty spectrum — short factual questions about live state that changes constantly. InfraNistic evaluates each query independently. Some resolve confidently on the fast tier; others require the power tier. This is correct behaviour, not instability. The escalation rate is the stable signal — it reflects the inherent difficulty distribution of your query mix.
🤖 Agentic Decision Bots
Autonomous agents that reason over structured inputs and produce decisions — not just answers
Agentic bots don't ask questions — they reason over data and decide what to do next. InfraNistic routes each reasoning step to the appropriate model tier based on the complexity of the input, not the type of agent.
Straightforward decisions resolve on the fast tier. Decisions that require deeper reasoning escalate to the power tier automatically. No rules to write, no thresholds to tune.
What this means for agentic workloads
An agent processing 1,000 decisions per day will not escalate all 1,000 to the expensive model. InfraNistic identifies which decisions genuinely require deeper reasoning and routes only those. The rest resolve cheaply and quickly. No rules to write. No thresholds to tune.
Model-agnostic by design: InfraNistic does not know what kind of agent is calling it. It evaluates the complexity of each input and routes accordingly. The same endpoint handles knowledge queries, status checks, and structured reasoning inputs — each gets the right model tier automatically.
Summary — All Bot Types
InfraNistic Standard, production endpoint, live measurements
| Bot Type | Key Behaviour | Typical Saving vs Large-Only |
|---|---|---|
| Knowledge bot | 39× speedup on warm queries, 0 escalations | ~87% |
| Status polling bot | Stable ~35% escalation rate, p95 < 9s at burst | ~87% |
| Agentic decision bot | Complexity-driven routing per decision step | Workload-dependent |
All measurements taken on the InfraNistic Standard tier against a production AWS Lambda endpoint. No warm-up, no cherry-picking. Cold start included in knowledge bot pass 1 numbers.
Deploy in one click
InfraNistic drops into your existing stack via AWS Marketplace.
Every bot query is automatically optimized from the first call.
$0.50 per 1,000 queries.